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ОС","\u002Fcsharp\u002Fsystem-programming-windows\u002Fwindows-hooks-services","01.csharp\u002F07.system-programming-windows\u002F20.windows-hooks-services",{"title":376,"path":377,"stem":378},"Системне Програмування C# (Windows) — 07.system-programming-windows","\u002Fcsharp\u002Fsystem-programming-windows\u002Fimplementation_plan","01.csharp\u002F07.system-programming-windows\u002Fimplementation_plan",{"title":380,"icon":132,"path":381,"stem":382,"children":383,"page":59},"Io","\u002Fcsharp\u002Fio","01.csharp\u002F08.io",[384,388,392,396,400],{"title":385,"path":386,"stem":387},"8.1.1. Основи роботи з файловою системою","\u002Fcsharp\u002Fio\u002Ffile-system-basics","01.csharp\u002F08.io\u002F01.file-system-basics",{"title":389,"path":390,"stem":391},"8.1.2. Потоки (Streams) та Серіалізація Даних","\u002Fcsharp\u002Fio\u002Fstreams-serialization","01.csharp\u002F08.io\u002F02.streams-serialization",{"title":393,"path":394,"stem":395},"8.2.1. JSON Serialization з System.Text.Json","\u002Fcsharp\u002Fio\u002Fjson-serialization","01.csharp\u002F08.io\u002F03.json-serialization",{"title":397,"path":398,"stem":399},"8.2.2. XML Serialization та LINQ to XML","\u002Fcsharp\u002Fio\u002Fxml-serialization","01.csharp\u002F08.io\u002F04.xml-serialization",{"title":401,"path":402,"stem":403},"8.2.3. Binary Serialization: MessagePack та Protocol Buffers","\u002Fcsharp\u002Fio\u002Fbinary-serialization","01.csharp\u002F08.io\u002F05.binary-serialization",{"title":405,"icon":132,"path":406,"stem":407,"children":408,"page":59},"Ado Net","\u002Fcsharp\u002Fado-net","01.csharp\u002F09.ado-net",[409,413,417,421,425,429,433,437,441,445,449,453],{"title":410,"path":411,"stem":412},"9.1. Введення в ADO.NET","\u002Fcsharp\u002Fado-net\u002Fintroduction-to-adonet","01.csharp\u002F09.ado-net\u002F01.introduction-to-adonet",{"title":414,"path":415,"stem":416},"9.2. Клас DbConnection — з'єднання з базою даних","\u002Fcsharp\u002Fado-net\u002Fconnection","01.csharp\u002F09.ado-net\u002F02.connection",{"title":418,"path":419,"stem":420},"9.3. Клас DbCommand — виконання SQL-запитів","\u002Fcsharp\u002Fado-net\u002Fcommand-and-queries","01.csharp\u002F09.ado-net\u002F03.command-and-queries",{"title":422,"path":423,"stem":424},"9.4. Клас DbDataReader — ефективне читання даних","\u002Fcsharp\u002Fado-net\u002Fdatareader","01.csharp\u002F09.ado-net\u002F04.datareader",{"title":426,"path":427,"stem":428},"9.5. Параметризовані запити та захист від SQL Injection","\u002Fcsharp\u002Fado-net\u002Fparameters-and-sql-injection","01.csharp\u002F09.ado-net\u002F05.parameters-and-sql-injection",{"title":430,"path":431,"stem":432},"9.6. Транзакції в ADO.NET","\u002Fcsharp\u002Fado-net\u002Ftransactions","01.csharp\u002F09.ado-net\u002F06.transactions",{"title":434,"path":435,"stem":436},"9.7. DbProviderFactory — провайдер-незалежний код","\u002Fcsharp\u002Fado-net\u002Fprovider-factory","01.csharp\u002F09.ado-net\u002F07.provider-factory",{"title":438,"path":439,"stem":440},"9.8. Асинхронний доступ до даних","\u002Fcsharp\u002Fado-net\u002Fasync-data-access","01.csharp\u002F09.ado-net\u002F08.async-data-access",{"title":442,"path":443,"stem":444},"9.9. Від'єднаний режим: DataSet, DataTable, DataRow","\u002Fcsharp\u002Fado-net\u002Fdisconnected-mode-dataset","01.csharp\u002F09.ado-net\u002F09.disconnected-mode-dataset",{"title":446,"path":447,"stem":448},"9.10. DataAdapter — міст між DataSet та базою даних","\u002Fcsharp\u002Fado-net\u002Fdata-adapter","01.csharp\u002F09.ado-net\u002F10.data-adapter",{"title":450,"path":451,"stem":452},"9.11. Data Mapper та Repository: Архітектура доступу до даних","\u002Fcsharp\u002Fado-net\u002Fdata-mapper-repository","01.csharp\u002F09.ado-net\u002F11.data-mapper-repository",{"title":454,"path":455,"stem":456},"9.12. Identity Map, Unit of Work та Specification Pattern","\u002Fcsharp\u002Fado-net\u002Fadvanced-patterns","01.csharp\u002F09.ado-net\u002F12.advanced-patterns",{"title":458,"icon":255,"path":459,"stem":460,"children":461,"page":59},"Ef Core","\u002Fcsharp\u002Fef-core","01.csharp\u002F10.ef-core",[462,466,470,474,478,482,486,490,494,498,502,506,510,514,518,522,526,532,538,542,546,550,554,558,562,566,570,574,578,582,586,590,594,598,602,606,610,614,618,622,626,630,634,638,642,646],{"title":463,"path":464,"stem":465},"Що таке ORM? Від SQL до об'єктів","\u002Fcsharp\u002Fef-core\u002Fwhat-is-orm","01.csharp\u002F10.ef-core\u002F01.what-is-orm",{"title":467,"path":468,"stem":469},"Перший проєкт — від нуля до CRUD","\u002Fcsharp\u002Fef-core\u002Ffirst-project","01.csharp\u002F10.ef-core\u002F02.first-project",{"title":471,"path":472,"stem":473},"DbContext — Серце EF Core","\u002Fcsharp\u002Fef-core\u002Fdbcontext-deep-dive","01.csharp\u002F10.ef-core\u002F03.dbcontext-deep-dive",{"title":475,"path":476,"stem":477},"Провайдери баз даних — Архітектура та Вибір СУБД","\u002Fcsharp\u002Fef-core\u002Fdatabase-providers","01.csharp\u002F10.ef-core\u002F04.database-providers",{"title":479,"path":480,"stem":481},"Конвенції EF Core — Магія без конфігурації","\u002Fcsharp\u002Fef-core\u002Fconventions","01.csharp\u002F10.ef-core\u002F05.conventions",{"title":483,"path":484,"stem":485},"Fluent API та Data Annotations — Явна конфігурація моделі","\u002Fcsharp\u002Fef-core\u002Ffluent-api-vs-annotations","01.csharp\u002F10.ef-core\u002F06.fluent-api-vs-annotations",{"title":487,"path":488,"stem":489},"Зв'язки — One-to-One та One-to-Many","\u002Fcsharp\u002Fef-core\u002Frelationships-basics","01.csharp\u002F10.ef-core\u002F07.relationships-basics",{"title":491,"path":492,"stem":493},"Зв'язки Advanced — Many-to-Many та Складні Сценарії","\u002Fcsharp\u002Fef-core\u002Frelationships-advanced","01.csharp\u002F10.ef-core\u002F08.relationships-advanced",{"title":495,"path":496,"stem":497},"Властивості — Типи, Конвертери, Компаратори (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fproperty-configuration-part1","01.csharp\u002F10.ef-core\u002F09.property-configuration-part1",{"title":499,"path":500,"stem":501},"Властивості — Value Comparers, Generators, Shadow Properties (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fproperty-configuration-part2","01.csharp\u002F10.ef-core\u002F09.property-configuration-part2",{"title":503,"path":504,"stem":505},"Складні типи — Owned Types та Complex Types (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fcomplex-types-owned-part1","01.csharp\u002F10.ef-core\u002F10.complex-types-owned-part1",{"title":507,"path":508,"stem":509},"Складні типи — Complex Types, Keyless Entities, Порівняння (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fcomplex-types-owned-part2","01.csharp\u002F10.ef-core\u002F10.complex-types-owned-part2",{"title":511,"path":512,"stem":513},"JSON Columns — Складні дані у JSON (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fjson-columns-part1","01.csharp\u002F10.ef-core\u002F11.json-columns-part1",{"title":515,"path":516,"stem":517},"JSON Columns — Value Comparers, Індекси, Провайдери (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fjson-columns-part2","01.csharp\u002F10.ef-core\u002F11.json-columns-part2",{"title":519,"path":520,"stem":521},"Успадкування — Абстрактні класи та TPH (Частина 1)","\u002Fcsharp\u002Fef-core\u002Finheritance-part1","01.csharp\u002F10.ef-core\u002F12.inheritance-part1",{"title":523,"path":524,"stem":525},"Успадкування — TPT, TPC та Порівняння Стратегій (Частина 2)","\u002Fcsharp\u002Fef-core\u002Finheritance-part2","01.csharp\u002F10.ef-core\u002F12.inheritance-part2",{"title":527,"path":528,"stem":529,"children":530},"Індекси, Обмеження та Схема (Частина 1)","\u002Fcsharp\u002Fef-core\u002Findexes-constraints-part1","01.csharp\u002F10.ef-core\u002F13.indexes-constraints-part1",[531],{"title":527,"path":528,"stem":529},{"title":533,"path":534,"stem":535,"children":536},"Індекси, Обмеження та Схема (Частина 2)","\u002Fcsharp\u002Fef-core\u002Findexes-constraints-part2","01.csharp\u002F10.ef-core\u002F13.indexes-constraints-part2",[537],{"title":533,"path":534,"stem":535},{"title":539,"path":540,"stem":541},"Seed Data — Початкові Дані (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fseeding-part1","01.csharp\u002F10.ef-core\u002F14.seeding-part1",{"title":543,"path":544,"stem":545},"Seed Data — SQL-скрипти, Bogus та Стратегії (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fseeding-part2","01.csharp\u002F10.ef-core\u002F14.seeding-part2",{"title":547,"path":548,"stem":549},"Global Query Filters — Глобальні Фільтри (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fglobal-query-filters-part1","01.csharp\u002F10.ef-core\u002F15.global-query-filters-part1",{"title":551,"path":552,"stem":553},"Global Query Filters — Підводні камені та Інтеграція (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fglobal-query-filters-part2","01.csharp\u002F10.ef-core\u002F15.global-query-filters-part2",{"title":555,"path":556,"stem":557},"LINQ-запити в EF Core (Частина 1)","\u002Fcsharp\u002Fef-core\u002Flinq-queries-part1","01.csharp\u002F10.ef-core\u002F16.linq-queries-part1",{"title":559,"path":560,"stem":561},"LINQ-запити в EF Core (Частина 2)","\u002Fcsharp\u002Fef-core\u002Flinq-queries-part2","01.csharp\u002F10.ef-core\u002F16.linq-queries-part2",{"title":563,"path":564,"stem":565},"Завантаження Пов'язаних Даних (Частина 1)","\u002Fcsharp\u002Fef-core\u002Floading-related-data-part1","01.csharp\u002F10.ef-core\u002F17.loading-related-data-part1",{"title":567,"path":568,"stem":569},"Завантаження Пов'язаних Даних (Частина 2)","\u002Fcsharp\u002Fef-core\u002Floading-related-data-part2","01.csharp\u002F10.ef-core\u002F17.loading-related-data-part2",{"title":571,"path":572,"stem":573},"Raw SQL, Views та Stored Procedures (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fraw-sql-part1","01.csharp\u002F10.ef-core\u002F18.raw-sql-part1",{"title":575,"path":576,"stem":577},"Raw SQL — Stored Procedures, DbFunction та Bulk Operations (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fraw-sql-part2","01.csharp\u002F10.ef-core\u002F18.raw-sql-part2",{"title":579,"path":580,"stem":581},"Продвинуті Запити — Compiled Queries, Bulk та Оптимізація (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fadvanced-queries-part1","01.csharp\u002F10.ef-core\u002F19.advanced-queries-part1",{"title":583,"path":584,"stem":585},"Продвинуті Запити — Query Tags, Bulk та Interceptors (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fadvanced-queries-part2","01.csharp\u002F10.ef-core\u002F19.advanced-queries-part2",{"title":587,"path":588,"stem":589},"Change Tracker — Відстеження Змін (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fchange-tracking-part1","01.csharp\u002F10.ef-core\u002F20.change-tracking-part1",{"title":591,"path":592,"stem":593},"Change Tracker — Графи Об'єктів та Disconnected (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fchange-tracking-part2","01.csharp\u002F10.ef-core\u002F20.change-tracking-part2",{"title":595,"path":596,"stem":597},"Збереження Даних та Транзакції (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fsaving-data-part1","01.csharp\u002F10.ef-core\u002F21.saving-data-part1",{"title":599,"path":600,"stem":601},"Збереження Даних — Concurrency та Outbox (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fsaving-data-part2","01.csharp\u002F10.ef-core\u002F21.saving-data-part2",{"title":603,"path":604,"stem":605},"Конкурентність та Блокування (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fconcurrency-part1","01.csharp\u002F10.ef-core\u002F22.concurrency-part1",{"title":607,"path":608,"stem":609},"Конкурентність — Дедлоки та Queue Processing (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fconcurrency-part2","01.csharp\u002F10.ef-core\u002F22.concurrency-part2",{"title":611,"path":612,"stem":613},"Міграції в EF Core — Основи (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fmigrations-basics-part1","01.csharp\u002F10.ef-core\u002F23.migrations-basics-part1",{"title":615,"path":616,"stem":617},"Міграції в EF Core — Основи (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fmigrations-basics-part2","01.csharp\u002F10.ef-core\u002F23.migrations-basics-part2",{"title":619,"path":620,"stem":621},"Міграції — Просунуті Сценарії (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fmigrations-advanced-part1","01.csharp\u002F10.ef-core\u002F24.migrations-advanced-part1",{"title":623,"path":624,"stem":625},"Міграції — Просунуті Сценарії (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fmigrations-advanced-part2","01.csharp\u002F10.ef-core\u002F24.migrations-advanced-part2",{"title":627,"path":628,"stem":629},"Управління Схемою та Database-First (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fschema-management-part1","01.csharp\u002F10.ef-core\u002F25.schema-management-part1",{"title":631,"path":632,"stem":633},"Управління Схемою та Database-First (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fschema-management-part2","01.csharp\u002F10.ef-core\u002F25.schema-management-part2",{"title":635,"path":636,"stem":637},"Продуктивність EF Core — Основи (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fperformance-fundamentals-part1","01.csharp\u002F10.ef-core\u002F26.performance-fundamentals-part1",{"title":639,"path":640,"stem":641},"Interceptors в EF Core (Частина 1)","\u002Fcsharp\u002Fef-core\u002Finterceptors-part1","01.csharp\u002F10.ef-core\u002F29.interceptors-part1",{"title":643,"path":644,"stem":645},"Interceptors в EF Core — Connection, Transaction та Materialization (Частина 2)","\u002Fcsharp\u002Fef-core\u002Finterceptors-part2","01.csharp\u002F10.ef-core\u002F29.interceptors-part2",{"title":647,"path":648,"stem":649},"План вивчення Entity Framework Core — Повний курс","\u002Fcsharp\u002Fef-core\u002Fimplementation_plan","01.csharp\u002F10.ef-core\u002Fimplementation_plan",{"title":651,"icon":652,"path":653,"stem":654,"children":655,"page":59},"ASP.NET","i-devicon-dotnetcore","\u002Fcsharp\u002Faspnet","01.csharp\u002F11.aspnet",[656,730,791,869,927,941,967,1057,1111,1182,1212,1289,1346],{"title":657,"icon":658,"path":659,"stem":660,"children":661,"page":59},"Minimal API","i-lucide-network","\u002Fcsharp\u002Faspnet\u002Fminimal-api","01.csharp\u002F11.aspnet\u002F01.minimal-api",[662,666,670,674,678,682,686,690,694,698,702,706,710,714,718,722,726],{"title":663,"path":664,"stem":665},"Вступ до ASP.NET та еволюція фреймворку","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fintroduction","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F01.introduction",{"title":667,"path":668,"stem":669},"Перший додаток на ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Ffirst-application","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F02.first-application",{"title":671,"path":672,"stem":673},"WebApplication, Builder та Dependency Injection","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fwebapplication-builder","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F03.webapplication-builder",{"title":675,"path":676,"stem":677},"Конвеєр запитів та Middleware","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Frequest-pipeline-middleware","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F04.request-pipeline-middleware",{"title":679,"path":680,"stem":681},"Маршрутизація в ASP.NET Core: Основи","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Frouting-basics","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F05.routing-basics",{"title":683,"path":684,"stem":685},"Маршрутизація в ASP.NET Core: Розширені можливості","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Frouting-advanced","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F06.routing-advanced",{"title":687,"path":688,"stem":689},"Статичні файли в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fstatic-files","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F07.static-files",{"title":691,"path":692,"stem":693},"Статичні Активи: MapStaticAssets (ASP.NET Core 9.0)","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fstatic-assets","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F08.static-assets",{"title":695,"path":696,"stem":697},"Конфігурація в ASP.NET Core: Основи","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fconfiguration-fundamentals","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F09.configuration-fundamentals",{"title":699,"path":700,"stem":701},"Конфігурація: Паттерн Options","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fconfiguration-options","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F10.configuration-options",{"title":703,"path":704,"stem":705},"Логування в ASP.NET Core: Основи","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Flogging-basics","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F11.logging-basics",{"title":707,"path":708,"stem":709},"Логування: Serilog та Middleware","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Flogging-advanced","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F12.logging-advanced",{"title":711,"path":712,"stem":713},"Управління станом: HttpContext.Items та Cookies","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fstate-management","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F13.state-management",{"title":715,"path":716,"stem":717},"Стан сесії: Sessions","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fsession-state","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F14.session-state",{"title":719,"path":720,"stem":721},"Структура проєкту: від хаосу до архітектури","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fproject-structure","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F15.project-structure",{"title":723,"path":724,"stem":725},"Scalar у Minimal API: повний проєкт і Fluent OpenAPI","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fscalar-openapi-fluent","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F16.scalar-openapi-fluent",{"title":727,"path":728,"stem":729},"Swagger \u002F Swashbuckle у Minimal API: окремий класичний шлях","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fswagger-swashbuckle","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F17.swagger-swashbuckle",{"title":731,"icon":658,"path":732,"stem":733,"children":734,"page":59},"API","\u002Fcsharp\u002Faspnet\u002Fapi","01.csharp\u002F11.aspnet\u002F02.api",[735,739,743,747,751,755,759,763,767,771,775,779,783,787],{"title":736,"path":737,"stem":738},"Що таке API. Клієнт-серверна архітектура","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fwhat-is-api","01.csharp\u002F11.aspnet\u002F02.api\u002F01.what-is-api",{"title":740,"path":741,"stem":742},"Формати даних: JSON, XML, TOML та бінарні формати","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fdata-formats","01.csharp\u002F11.aspnet\u002F02.api\u002F02.data-formats",{"title":744,"path":745,"stem":746},"Парадигми API та концепція REST","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fapi-paradigms-rest","01.csharp\u002F11.aspnet\u002F02.api\u002F03.api-paradigms-rest",{"title":748,"path":749,"stem":750},"HTTP-методи, статус-коди та заголовки","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fhttp-methods-status-codes","01.csharp\u002F11.aspnet\u002F02.api\u002F04.http-methods-status-codes",{"title":752,"path":753,"stem":754},"Організація HTTP API за принципами REST","\u002Fcsharp\u002Faspnet\u002Fapi\u002Frest-organizing","01.csharp\u002F11.aspnet\u002F02.api\u002F05.rest-organizing",{"title":756,"path":757,"stem":758},"Номенклатура URL та CRUD-операції","\u002Fcsharp\u002Faspnet\u002Fapi\u002Furl-nomenclature-crud","01.csharp\u002F11.aspnet\u002F02.api\u002F06.url-nomenclature-crud",{"title":760,"path":761,"stem":762},"Правила дизайну: іменування та стандарти","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fapi-design-naming","01.csharp\u002F11.aspnet\u002F02.api\u002F07.api-design-naming",{"title":764,"path":765,"stem":766},"Валідація, ліміти та обробка помилок","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fapi-design-validation","01.csharp\u002F11.aspnet\u002F02.api\u002F08.api-design-validation",{"title":768,"path":769,"stem":770},"Обробка помилок у Minimal API","\u002Fcsharp\u002Faspnet\u002Fapi\u002Ferror-handling-http","01.csharp\u002F11.aspnet\u002F02.api\u002F09.error-handling-http",{"title":772,"path":773,"stem":774},"Ідемпотентність та синхронізація стану","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fidempotency-sync","01.csharp\u002F11.aspnet\u002F02.api\u002F10.idempotency-sync",{"title":776,"path":777,"stem":778},"Пагінація та організація списків","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fpagination-lists","01.csharp\u002F11.aspnet\u002F02.api\u002F11.pagination-lists",{"title":780,"path":781,"stem":782},"Безпека API, кешування та інтернаціоналізація","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fsecurity-auth","01.csharp\u002F11.aspnet\u002F02.api\u002F12.security-auth",{"title":784,"path":785,"stem":786},"Процес проєктування API та документування","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fapi-design-process","01.csharp\u002F11.aspnet\u002F02.api\u002F13.api-design-process",{"title":788,"path":789,"stem":790},"OpenAPI: контракт, специфікація та документація API","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fopenapi","01.csharp\u002F11.aspnet\u002F02.api\u002F14.openapi",{"title":792,"icon":793,"path":794,"stem":795,"children":796,"page":59},"Auth","i-lucide-shield-check","\u002Fcsharp\u002Faspnet\u002Fauth","01.csharp\u002F11.aspnet\u002F03.auth",[797,801,805,809,813,817,821,825,829,833,837,841,845,849,853,857,861,865],{"title":798,"path":799,"stem":800},"Основи аутентифікації та авторизації","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fauth-fundamentals","01.csharp\u002F11.aspnet\u002F03.auth\u002F01.auth-fundamentals",{"title":802,"path":803,"stem":804},"JWT-аутентифікація","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fjwt-authentication","01.csharp\u002F11.aspnet\u002F03.auth\u002F02.jwt-authentication",{"title":806,"path":807,"stem":808},"Авторизація: ролі, політики та resource-based доступ","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fauthorization-policies","01.csharp\u002F11.aspnet\u002F03.auth\u002F03.authorization-policies",{"title":810,"path":811,"stem":812},"Cookie-аутентифікація та ASP.NET Core Identity","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fcookie-auth-identity","01.csharp\u002F11.aspnet\u002F03.auth\u002F04.cookie-auth-identity",{"title":814,"path":815,"stem":816},"JWT + Refresh Tokens (HttpOnly Cookie)","\u002Fcsharp\u002Faspnet\u002Fauth\u002F04b.identity-auth-jwt","01.csharp\u002F11.aspnet\u002F03.auth\u002F04b.identity-auth-jwt",{"title":818,"path":819,"stem":820},"Identity: Підтвердження Email та Скидання Пароля","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fidentity-email-confirmation","01.csharp\u002F11.aspnet\u002F03.auth\u002F05.identity-email-confirmation",{"title":822,"path":823,"stem":824},"Identity: Двофакторна Аутентифікація (2FA)","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fidentity-two-factor","01.csharp\u002F11.aspnet\u002F03.auth\u002F06.identity-two-factor",{"title":826,"path":827,"stem":828},"Identity: Внутрішня Архітектура та Кастомізація","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fidentity-internals","01.csharp\u002F11.aspnet\u002F03.auth\u002F07.identity-internals",{"title":830,"path":831,"stem":832},"OAuth 2.0 та зовнішні провайдери","\u002Fcsharp\u002Faspnet\u002Fauth\u002Foauth-external-providers","01.csharp\u002F11.aspnet\u002F03.auth\u002F08.oauth-external-providers",{"title":834,"path":835,"stem":836},"Безпека на практиці: CORS, HTTPS та захист від атак","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fsecurity-hardening","01.csharp\u002F11.aspnet\u002F03.auth\u002F09.security-hardening",{"title":838,"path":839,"stem":840},"Теорія OAuth 2.0: Поняття, Аналогії та Флоу","\u002Fcsharp\u002Faspnet\u002Fauth\u002Foauth-theory","01.csharp\u002F11.aspnet\u002F03.auth\u002F10.oauth-theory",{"title":842,"path":843,"stem":844},"OIDC, OAuth 2.0 та Keycloak в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Foidc-keycloak","01.csharp\u002F11.aspnet\u002F03.auth\u002F10.oidc-keycloak",{"title":846,"path":847,"stem":848},"API Keys аутентифікація в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fapi-keys","01.csharp\u002F11.aspnet\u002F03.auth\u002F11.api-keys",{"title":850,"path":851,"stem":852},"Rate Limiting та Throttling в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Frate-limiting","01.csharp\u002F11.aspnet\u002F03.auth\u002F12.rate-limiting",{"title":854,"path":855,"stem":856},"Refresh Token Rotation в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Frefresh-token-rotation","01.csharp\u002F11.aspnet\u002F03.auth\u002F13.refresh-token-rotation",{"title":858,"path":859,"stem":860},"Certificate Authentication та mTLS в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fcertificate-auth","01.csharp\u002F11.aspnet\u002F03.auth\u002F14.certificate-auth",{"title":862,"path":863,"stem":864},"RBAC, ABAC та ReBAC в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Frbac-abac-rebac","01.csharp\u002F11.aspnet\u002F03.auth\u002F15.rbac-abac-rebac",{"title":866,"path":867,"stem":868},"Multi-tenancy та ізоляція даних в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fmulti-tenancy","01.csharp\u002F11.aspnet\u002F03.auth\u002F16.multi-tenancy",{"title":870,"icon":871,"path":872,"stem":873,"children":874,"page":59},"Нотифікації","i-lucide-bell","\u002Fcsharp\u002Faspnet\u002Fnotifications","01.csharp\u002F11.aspnet\u002F04.notifications",[875,879,883,887,891,895,899,903,907,911,915,919,923],{"title":876,"path":877,"stem":878},"In-App нотифікації через базу даних","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fin-app-database-notifications","01.csharp\u002F11.aspnet\u002F04.notifications\u002F01.in-app-database-notifications",{"title":880,"path":881,"stem":882},"Polling: Регулярний запит оновлень","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fpolling","01.csharp\u002F11.aspnet\u002F04.notifications\u002F02.polling",{"title":884,"path":885,"stem":886},"Server-Sent Events: Однострімовий push від сервера","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fserver-sent-events","01.csharp\u002F11.aspnet\u002F04.notifications\u002F03.server-sent-events",{"title":888,"path":889,"stem":890},"WebSockets: Двостороннє з'єднання в реальному часі","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fwebsockets","01.csharp\u002F11.aspnet\u002F04.notifications\u002F04.websockets",{"title":892,"path":893,"stem":894},"SignalR: Абстракція над транспортами реального часу","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fsignalr","01.csharp\u002F11.aspnet\u002F04.notifications\u002F05.signalr",{"title":896,"path":897,"stem":898},"Background Services: Фонові задачі в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fbackground-services","01.csharp\u002F11.aspnet\u002F04.notifications\u002F06.background-services",{"title":900,"path":901,"stem":902},"Web Push нотифікації","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fweb-push","01.csharp\u002F11.aspnet\u002F04.notifications\u002F07.web-push",{"title":904,"path":905,"stem":906},"Email нотифікації","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Femail-notifications","01.csharp\u002F11.aspnet\u002F04.notifications\u002F08.email-notifications",{"title":908,"path":909,"stem":910},"Порівняння підходів: Як вибрати правильну технологію нотифікацій","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fchoosing-the-right-approach","01.csharp\u002F11.aspnet\u002F04.notifications\u002F09.choosing-the-right-approach",{"title":912,"path":913,"stem":914},"Hangfire: Надійне планування фонових задач","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fhangfire","01.csharp\u002F11.aspnet\u002F04.notifications\u002F10.hangfire",{"title":916,"path":917,"stem":918},"Практика: Конвертація зображень у WebP через Hangfire","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fhangfire-image-webp","01.csharp\u002F11.aspnet\u002F04.notifications\u002F11.hangfire-image-webp",{"title":920,"path":921,"stem":922},"Практика: Підготовка відео до HLS-стрімінгу через Hangfire","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fhangfire-video-hls","01.csharp\u002F11.aspnet\u002F04.notifications\u002F12.hangfire-video-hls",{"title":924,"path":925,"stem":926},"Telegram-нотифікації: від одного повідомлення до масових розсилок і мульти-канального підходу","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Ftelegram-notifications","01.csharp\u002F11.aspnet\u002F04.notifications\u002F13.telegram-notifications",{"title":928,"icon":929,"path":930,"stem":931,"children":932,"page":59},"Інтернаціоналізація","i-lucide-languages","\u002Fcsharp\u002Faspnet\u002Fi18n","01.csharp\u002F11.aspnet\u002F05.i18n",[933,937],{"title":934,"path":935,"stem":936},"Інтернаціоналізація (i18n) у Minimal API: від A до Я","\u002Fcsharp\u002Faspnet\u002Fi18n\u002Finternationalization","01.csharp\u002F11.aspnet\u002F05.i18n\u002F01.internationalization",{"title":938,"path":939,"stem":940},"Humanizer: людиномовні рядки у .NET","\u002Fcsharp\u002Faspnet\u002Fi18n\u002Fhumanizer","01.csharp\u002F11.aspnet\u002F05.i18n\u002F02.humanizer",{"title":942,"icon":943,"path":944,"stem":945,"children":946,"page":59},"Кешування","i-lucide-layers","\u002Fcsharp\u002Faspnet\u002Fcaching","01.csharp\u002F11.aspnet\u002F06.caching",[947,951,955,959,963],{"title":948,"path":949,"stem":950},"Огляд кешування: чотири рівні і коли що обирати","\u002Fcsharp\u002Faspnet\u002Fcaching\u002Fcaching","01.csharp\u002F11.aspnet\u002F06.caching\u002F01.caching",{"title":952,"path":953,"stem":954},"IMemoryCache: кеш в оперативній пам'яті","\u002Fcsharp\u002Faspnet\u002Fcaching\u002Fmemory-cache","01.csharp\u002F11.aspnet\u002F06.caching\u002F02.memory-cache",{"title":956,"path":957,"stem":958},"IDistributedCache і Redis: розподілений кеш","\u002Fcsharp\u002Faspnet\u002Fcaching\u002Fdistributed-cache","01.csharp\u002F11.aspnet\u002F06.caching\u002F03.distributed-cache",{"title":960,"path":961,"stem":962},"Response Cache: HTTP-кешування через Cache-Control","\u002Fcsharp\u002Faspnet\u002Fcaching\u002Fresponse-cache","01.csharp\u002F11.aspnet\u002F06.caching\u002F04.response-cache",{"title":964,"path":965,"stem":966},"Output Cache: серверний кеш HTTP-відповідей (.NET 7+)","\u002Fcsharp\u002Faspnet\u002Fcaching\u002Foutput-cache","01.csharp\u002F11.aspnet\u002F06.caching\u002F05.output-cache",{"title":968,"icon":969,"path":970,"stem":971,"children":972,"page":59},"Тестування","i-lucide-test-tube","\u002Fcsharp\u002Faspnet\u002Ftesting","01.csharp\u002F11.aspnet\u002F07.testing",[973,977,981,985,989,993,997,1001,1005,1009,1013,1017,1021,1025,1029,1033,1037,1041,1045,1049,1053],{"title":974,"path":975,"stem":976},"Що таке тестування? Від інтуїції до науки","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fwhat-is-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F01.what-is-testing",{"title":978,"path":979,"stem":980},"Піраміда тестування — Стратегія, а не Догма","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Ftesting-pyramid","01.csharp\u002F11.aspnet\u002F07.testing\u002F02.testing-pyramid",{"title":982,"path":983,"stem":984},"Дві Школи Тестування — Лондон проти Детройту","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Ftesting-schools","01.csharp\u002F11.aspnet\u002F07.testing\u002F03.testing-schools",{"title":986,"path":987,"stem":988},"TDD та BDD — Тести як Дизайн-інструмент","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Ftdd-and-bdd","01.csharp\u002F11.aspnet\u002F07.testing\u002F04.tdd-and-bdd",{"title":990,"path":991,"stem":992},"Що саме тестувати — Техніки аналізу та Циклomatична складність","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fwhat-to-test","01.csharp\u002F11.aspnet\u002F07.testing\u002F05.what-to-test",{"title":994,"path":995,"stem":996},"Тестові Фреймворки — Навіщо вони і що всередині","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Ftest-frameworks","01.csharp\u002F11.aspnet\u002F07.testing\u002F06.test-frameworks",{"title":998,"path":999,"stem":1000},"xUnit — Факти, Теорії та Lifecycle тестів","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fxunit-basics","01.csharp\u002F11.aspnet\u002F07.testing\u002F07.xunit-basics",{"title":1002,"path":1003,"stem":1004},"xUnit Advanced — Fixtures, Кастомізація та Розширення","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fxunit-advanced","01.csharp\u002F11.aspnet\u002F07.testing\u002F08.xunit-advanced",{"title":1006,"path":1007,"stem":1008},"Moq — Глибоке занурення в мокування","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fmocking-with-moq","01.csharp\u002F11.aspnet\u002F07.testing\u002F09.mocking-with-moq",{"title":1010,"path":1011,"stem":1012},"Тестування Баз Даних — EF Core, SQLite та Testcontainers","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fdatabase-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F10.database-testing",{"title":1014,"path":1015,"stem":1016},"Integration Testing — Частина 1 [Теорія та WebApplicationFactory]","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fintegration-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F11.integration-testing",{"title":1018,"path":1019,"stem":1020},"Інтеграційне тестування — Практика","\u002Fcsharp\u002Faspnet\u002Ftesting\u002F11a.integration-testing-practice","01.csharp\u002F11.aspnet\u002F07.testing\u002F11a.integration-testing-practice",{"title":1022,"path":1023,"stem":1024},"Integration Testing — Частина 2 [Просунуті Сценарії та Testcontainers]","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fintegration-testing-advanced","01.csharp\u002F11.aspnet\u002F07.testing\u002F12.integration-testing-advanced",{"title":1026,"path":1027,"stem":1028},"Професійний Postman: Колекції, Змінні та GitHub Інтеграція","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fpostman-professional","01.csharp\u002F11.aspnet\u002F07.testing\u002F13.postman-professional",{"title":1030,"path":1031,"stem":1032},"HttpClient у Тестах Частина 1: Архітектура та MockHttpMessageHandler","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fhttpclient-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F14.httpclient-testing",{"title":1034,"path":1035,"stem":1036},"HttpClient у Тестах Частина 2: WireMock.Net та Resilience","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fwiremock-net","01.csharp\u002F11.aspnet\u002F07.testing\u002F15.wiremock-net",{"title":1038,"path":1039,"stem":1040},"Патерни та Анти-патерни Тестування: Test Smells","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Ftesting-patterns","01.csharp\u002F11.aspnet\u002F07.testing\u002F16.testing-patterns",{"title":1042,"path":1043,"stem":1044},"Просунуті інструменти: Time, Snapshots та Властивості","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fadvanced-testing-tools","01.csharp\u002F11.aspnet\u002F07.testing\u002F17.advanced-testing-tools",{"title":1046,"path":1047,"stem":1048},"Тестування Архітектури з NetArchTest","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Farchitecture-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F18.architecture-testing",{"title":1050,"path":1051,"stem":1052},"Тестування Продуктивності: BenchmarkDotNet, NBomber та k6","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fperformance-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F19.performance-testing",{"title":1054,"path":1055,"stem":1056},"Залишок плану для курсу \"Тестування ASP.NET Minimal API\"","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fremaining_plan","01.csharp\u002F11.aspnet\u002F07.testing\u002Fremaining_plan",{"title":1058,"icon":1059,"path":1060,"stem":1061,"children":1062,"page":59},"Платежі","i-lucide-credit-card","\u002Fcsharp\u002Faspnet\u002Fpayments","01.csharp\u002F11.aspnet\u002F08.payments",[1063,1067,1071,1075,1079,1083,1087,1091,1095,1099,1103,1107],{"title":1064,"path":1065,"stem":1066},"Основи платіжної інфраструктури","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fpayment-fundamentals","01.csharp\u002F11.aspnet\u002F08.payments\u002F01.payment-fundamentals",{"title":1068,"path":1069,"stem":1070},"Методи оплати в Україні","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fpayment-methods-ukraine","01.csharp\u002F11.aspnet\u002F08.payments\u002F02.payment-methods-ukraine",{"title":1072,"path":1073,"stem":1074},"PCI DSS та безпека платежів","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fpci-dss-security","01.csharp\u002F11.aspnet\u002F08.payments\u002F03.pci-dss-security",{"title":1076,"path":1077,"stem":1078},"Архітектура платіжної підсистеми","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fpayment-architecture","01.csharp\u002F11.aspnet\u002F08.payments\u002F04.payment-architecture",{"title":1080,"path":1081,"stem":1082},"Інтеграція LiqPay (ПриватБанк)","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fliqpay-integration","01.csharp\u002F11.aspnet\u002F08.payments\u002F05.liqpay-integration",{"title":1084,"path":1085,"stem":1086},"Інтеграція Monobank Acquiring API","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fmonobank-acquiring","01.csharp\u002F11.aspnet\u002F08.payments\u002F06.monobank-acquiring",{"title":1088,"path":1089,"stem":1090},"Інтеграція Stripe","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fstripe-integration","01.csharp\u002F11.aspnet\u002F08.payments\u002F07.stripe-integration",{"title":1092,"path":1093,"stem":1094},"Webhooks — глибоке занурення","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fwebhooks-deep-dive","01.csharp\u002F11.aspnet\u002F08.payments\u002F08.webhooks-deep-dive",{"title":1096,"path":1097,"stem":1098},"Підписки та рекурентні платежі","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fsubscriptions-recurring","01.csharp\u002F11.aspnet\u002F08.payments\u002F09.subscriptions-recurring",{"title":1100,"path":1101,"stem":1102},"Повернення коштів та диспути","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Frefunds-disputes","01.csharp\u002F11.aspnet\u002F08.payments\u002F10.refunds-disputes",{"title":1104,"path":1105,"stem":1106},"Тестування платіжних інтеграцій","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Ftesting-payments","01.csharp\u002F11.aspnet\u002F08.payments\u002F11.testing-payments",{"title":1108,"path":1109,"stem":1110},"Чекліст виходу в Production","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fproduction-checklist","01.csharp\u002F11.aspnet\u002F08.payments\u002F12.production-checklist",{"title":1112,"icon":1113,"items":1114,"path":1127,"stem":1128,"children":1129,"page":59},"Популярні бібліотеки","lucide:box",[1115,1116,1117,1118,1119,1120,1121,1122,1123,1124,1125,1126],"01.fluent-validation","02.mapster","03.erroror-result-pattern","04.serilog","05.mediatr","06.polly","07.health-checks","08.feature-management","09.fluent-email","10.quest-pdf","11.bogus","12.humanizer-guard","\u002Fcsharp\u002Faspnet\u002Flibraries","01.csharp\u002F11.aspnet\u002F09.libraries",[1130,1134,1138,1142,1146,1150,1154,1158,1162,1166,1170,1174,1178],{"title":1131,"path":1132,"stem":1133},"Валідація з FluentValidation в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Ffluent-validation","01.csharp\u002F11.aspnet\u002F09.libraries\u002F01.fluent-validation",{"title":1135,"path":1136,"stem":1137},"Маппінг об","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fmapster","01.csharp\u002F11.aspnet\u002F09.libraries\u002F02.mapster",{"title":1139,"path":1140,"stem":1141},"Обробка помилок з ErrorOr та Result Pattern в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Ferroror-result-pattern","01.csharp\u002F11.aspnet\u002F09.libraries\u002F03.erroror-result-pattern",{"title":1143,"path":1144,"stem":1145},"Структуроване логування з Serilog в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fserilog","01.csharp\u002F11.aspnet\u002F09.libraries\u002F04.serilog",{"title":1147,"path":1148,"stem":1149},"CQRS та Mediator з MediatR в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fmediatr","01.csharp\u002F11.aspnet\u002F09.libraries\u002F05.mediatr",{"title":1151,"path":1152,"stem":1153},"Відмовостійкість з Polly в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fpolly","01.csharp\u002F11.aspnet\u002F09.libraries\u002F06.polly",{"title":1155,"path":1156,"stem":1157},"Health Checks в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fhealth-checks","01.csharp\u002F11.aspnet\u002F09.libraries\u002F07.health-checks",{"title":1159,"path":1160,"stem":1161},"Feature Management та Feature Flags в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Ffeature-management","01.csharp\u002F11.aspnet\u002F09.libraries\u002F08.feature-management",{"title":1163,"path":1164,"stem":1165},"Відправка Email з FluentEmail в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Ffluent-email","01.csharp\u002F11.aspnet\u002F09.libraries\u002F09.fluent-email",{"title":1167,"path":1168,"stem":1169},"Генерація PDF з QuestPDF в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fquest-pdf","01.csharp\u002F11.aspnet\u002F09.libraries\u002F10.quest-pdf",{"title":1171,"path":1172,"stem":1173},"Генерація тестових даних з Bogus в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fbogus","01.csharp\u002F11.aspnet\u002F09.libraries\u002F11.bogus",{"title":1175,"path":1176,"stem":1177},"Humanizer та Guard Clauses в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fhumanizer-guard","01.csharp\u002F11.aspnet\u002F09.libraries\u002F12.humanizer-guard",{"title":1179,"path":1180,"stem":1181},"План модуля 10.libraries — Популярні бібліотеки ASP.NET","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fplan","01.csharp\u002F11.aspnet\u002F09.libraries\u002Fplan",{"title":1183,"icon":1184,"path":1185,"stem":1186,"children":1187,"page":59},"Razor Pages","i-lucide-layout-template","\u002Fcsharp\u002Faspnet\u002Frazor-pages","01.csharp\u002F11.aspnet\u002F10.razor-pages",[1188,1192,1196,1200,1204,1208],{"title":1189,"path":1190,"stem":1191},"Від Minimal API до Razor Pages: концептуальний перехід","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Ffrom-minimal-api","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F01.from-minimal-api",{"title":1193,"path":1194,"stem":1195},"PageModel: логіка сторінки Razor Pages","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Fpage-model","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F02.page-model",{"title":1197,"path":1198,"stem":1199},"Razor синтаксис: шаблонізатор у .cshtml","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Frazor-syntax","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F03.razor-syntax",{"title":1201,"path":1202,"stem":1203},"Tag Helpers: типізований HTML","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Ftag-helpers","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F04.tag-helpers",{"title":1205,"path":1206,"stem":1207},"Форми і валідація: повний цикл обробки даних","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Fforms-validation","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F05.forms-validation",{"title":1209,"path":1210,"stem":1211},"Практичний проєкт: TaskManager на Razor Pages","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Fproject-task-manager","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F06.project-task-manager",{"title":1213,"path":1214,"stem":1215,"children":1216,"page":59},"ASP.NET Core MVC","\u002Fcsharp\u002Faspnet\u002Fmvc","01.csharp\u002F11.aspnet\u002F11.mvc",[1217,1221,1225,1229,1233,1237,1241,1245,1249,1253,1257,1261,1265,1269,1273,1277,1281,1285],{"title":1218,"path":1219,"stem":1220},"Патерн MVC: архітектура, що змінила веб","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fmvc-pattern","01.csharp\u002F11.aspnet\u002F11.mvc\u002F01.mvc-pattern",{"title":1222,"path":1223,"stem":1224},"Від Razor Pages до MVC: концептуальний перехід","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Ffrom-razor-pages","01.csharp\u002F11.aspnet\u002F11.mvc\u002F02.from-razor-pages",{"title":1226,"path":1227,"stem":1228},"Controllers та Actions: серце MVC","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fcontrollers-actions","01.csharp\u002F11.aspnet\u002F11.mvc\u002F03.controllers-actions",{"title":1230,"path":1231,"stem":1232},"Маршрутизація в MVC: Convention vs Attribute Routing","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Frouting-mvc","01.csharp\u002F11.aspnet\u002F11.mvc\u002F04.routing-mvc",{"title":1234,"path":1235,"stem":1236},"Model Binding: від HTTP до C#","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fmodel-binding","01.csharp\u002F11.aspnet\u002F11.mvc\u002F05.model-binding",{"title":1238,"path":1239,"stem":1240},"Views, ViewData, ViewBag, TempData і ViewModel","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fviews-viewdata-tempdata","01.csharp\u002F11.aspnet\u002F11.mvc\u002F06.views-viewdata-tempdata",{"title":1242,"path":1243,"stem":1244},"Filters: аспектно-орієнтоване програмування в MVC","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Ffilters","01.csharp\u002F11.aspnet\u002F11.mvc\u002F07.filters",{"title":1246,"path":1247,"stem":1248},"Areas: структурування великих застосунків","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fareas","01.csharp\u002F11.aspnet\u002F11.mvc\u002F08.areas",{"title":1250,"path":1251,"stem":1252},"View Components: повторювані незалежні блоки UI","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fview-components","01.csharp\u002F11.aspnet\u002F11.mvc\u002F09.view-components",{"title":1254,"path":1255,"stem":1256},"Display та Editor Templates","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fdisplay-editor-templates","01.csharp\u002F11.aspnet\u002F11.mvc\u002F10.display-editor-templates",{"title":1258,"path":1259,"stem":1260},"Валідація: IValidatableObject та FluentValidation","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fvalidation-advanced","01.csharp\u002F11.aspnet\u002F11.mvc\u002F11.validation-advanced",{"title":1262,"path":1263,"stem":1264},"HTMX: інтерактивність через HTML-атрибути","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fhtmx","01.csharp\u002F11.aspnet\u002F11.mvc\u002F12.htmx",{"title":1266,"path":1267,"stem":1268},"HTMX у ASP.NET Core MVC: серверна інтеграція","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fajax-htmx-mvc","01.csharp\u002F11.aspnet\u002F11.mvc\u002F13.ajax-htmx-mvc",{"title":1270,"path":1271,"stem":1272},"Практичний проєкт: Каталог товарів з HTMX","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fhtmx-project","01.csharp\u002F11.aspnet\u002F11.mvc\u002F14.htmx-project",{"title":1274,"path":1275,"stem":1276},"Завантаження та обробка файлів","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Ffile-upload","01.csharp\u002F11.aspnet\u002F11.mvc\u002F15.file-upload",{"title":1278,"path":1279,"stem":1280},"Глобалізація та Локалізація MVC","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fglobalization-localization","01.csharp\u002F11.aspnet\u002F11.mvc\u002F16.globalization-localization",{"title":1282,"path":1283,"stem":1284},"Підсумковий проєкт: Блог-платформа","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fmvc-project","01.csharp\u002F11.aspnet\u002F11.mvc\u002F17.mvc-project",{"title":1286,"path":1287,"stem":1288},"План курсу: ASP.NET Core MVC","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fplan","01.csharp\u002F11.aspnet\u002F11.mvc\u002Fplan",{"title":1290,"path":1291,"stem":1292,"children":1293,"page":59},"Web Api","\u002Fcsharp\u002Faspnet\u002Fweb-api","01.csharp\u002F11.aspnet\u002F12.web-api",[1294,1298,1302,1306,1310,1314,1318,1322,1326,1330,1334,1338,1342],{"title":1295,"path":1296,"stem":1297},"Від Minimal API до Controller-based API","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Ffrom-minimal-api-to-controllers","01.csharp\u002F11.aspnet\u002F12.web-api\u002F01.from-minimal-api-to-controllers",{"title":1299,"path":1300,"stem":1301},"ControllerBase, ActionResult\u003CT> та Response Types","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fcontroller-base-actionresult","01.csharp\u002F11.aspnet\u002F12.web-api\u002F02.controller-base-actionresult",{"title":1303,"path":1304,"stem":1305},"Content Negotiation - JSON, XML та власні форматери","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fcontent-negotiation","01.csharp\u002F11.aspnet\u002F12.web-api\u002F03.content-negotiation",{"title":1307,"path":1308,"stem":1309},"Версіонування API","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fapi-versioning","01.csharp\u002F11.aspnet\u002F12.web-api\u002F04.api-versioning",{"title":1311,"path":1312,"stem":1313},"ProblemDetails та структурована обробка помилок","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fproblemdetails-error-handling","01.csharp\u002F11.aspnet\u002F12.web-api\u002F05.problemdetails-error-handling",{"title":1315,"path":1316,"stem":1317},"Фільтри у Web API контексті","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Ffilters-for-api","01.csharp\u002F11.aspnet\u002F12.web-api\u002F06.filters-for-api",{"title":1319,"path":1320,"stem":1321},"Пагінація, фільтрація та сортування","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fpagination-filtering-sorting","01.csharp\u002F11.aspnet\u002F12.web-api\u002F07.pagination-filtering-sorting",{"title":1323,"path":1324,"stem":1325},"HATEOAS та Resource Expansion","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fhateoas-resource-expansion","01.csharp\u002F11.aspnet\u002F12.web-api\u002F08.hateoas-resource-expansion",{"title":1327,"path":1328,"stem":1329},"Гібридна архітектура - Minimal API + Controllers","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fminimal-api-vs-controllers-hybrid","01.csharp\u002F11.aspnet\u002F12.web-api\u002F09.minimal-api-vs-controllers-hybrid",{"title":1331,"path":1332,"stem":1333},"Документація API - Swashbuckle, NSwag та генерація клієнтів","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fapi-documentation-generation","01.csharp\u002F11.aspnet\u002F12.web-api\u002F10.api-documentation-generation",{"title":1335,"path":1336,"stem":1337},"Health Checks та моніторинг API","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fhealth-checks-monitoring","01.csharp\u002F11.aspnet\u002F12.web-api\u002F11.health-checks-monitoring",{"title":1339,"path":1340,"stem":1341},"Підсумковий проєкт - Production-Ready REST API","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fweb-api-project","01.csharp\u002F11.aspnet\u002F12.web-api\u002F12.web-api-project",{"title":1343,"path":1344,"stem":1345},"План курсу: ASP.NET Core Web API (Controllers)","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fplan","01.csharp\u002F11.aspnet\u002F12.web-api\u002Fplan",{"title":1347,"icon":1348,"path":1349,"stem":1350,"children":1351,"page":59},"Моніторинг","i-lucide-activity","\u002Fcsharp\u002Faspnet\u002Fmonitoring","01.csharp\u002F11.aspnet\u002F13.monitoring",[1352,1356,1360],{"title":1353,"path":1354,"stem":1355},"Спостережуваність: від console.log до production-систем","\u002Fcsharp\u002Faspnet\u002Fmonitoring\u002Fobservability-intro","01.csharp\u002F11.aspnet\u002F13.monitoring\u002F01.observability-intro",{"title":1357,"path":1358,"stem":1359},"Health Checks: перший рівень observability","\u002Fcsharp\u002Faspnet\u002Fmonitoring\u002Fhealth-checks","01.csharp\u002F11.aspnet\u002F13.monitoring\u002F02.health-checks",{"title":1361,"path":1362,"stem":1363},"Вбудовані метрики .NET 10 та System.Diagnostics.Metrics","\u002Fcsharp\u002Faspnet\u002Fmonitoring\u002Fdotnet-metrics","01.csharp\u002F11.aspnet\u002F13.monitoring\u002F03.dotnet-metrics",{"title":1365,"icon":1366,"path":1367,"stem":1368,"children":1369,"page":59},"Desktop UI","i-lucide-app-window","\u002Fcsharp\u002Fdesktop-ui","01.csharp\u002F12.desktop-ui",[1370,1374,1378,1382,1386,1390,1394,1398,1402,1406,1410,1414,1418,1422,1426,1430,1434,1438,1442,1446,1450,1454,1458,1462,1466,1470,1474,1478,1482,1486,1490,1494,1498,1502,1506,1510,1514,1518,1522,1526,1530,1534,1538,1542,1546,1550,1554,1558,1562,1566,1570,1574,1578,1582,1586,1590,1594,1598,1602,1606,1610,1614,1618,1622,1626,1630,1634,1638,1642,1646,1650],{"title":1371,"path":1372,"stem":1373},"Що таке десктопна розробка?","\u002Fcsharp\u002Fdesktop-ui\u002Fwhat-is-desktop-dev","01.csharp\u002F12.desktop-ui\u002F01.what-is-desktop-dev",{"title":1375,"path":1376,"stem":1377},"Архітектура WPF — як влаштований графічний інтерфейс","\u002Fcsharp\u002Fdesktop-ui\u002Fwpf-architecture","01.csharp\u002F12.desktop-ui\u002F02.wpf-architecture",{"title":1379,"path":1380,"stem":1381},"Перший WPF-проєкт — від нуля до вікна","\u002Fcsharp\u002Fdesktop-ui\u002Ffirst-wpf-app","01.csharp\u002F12.desktop-ui\u002F03.first-wpf-app",{"title":1383,"path":1384,"stem":1385},"Перший Avalonia-проєкт: WPF для всіх платформ","\u002Fcsharp\u002Fdesktop-ui\u002F03a.first-avalonia-app","01.csharp\u002F12.desktop-ui\u002F03a.first-avalonia-app",{"title":1387,"path":1388,"stem":1389},"XAML: декларативний інтерфейс","\u002Fcsharp\u002Fdesktop-ui\u002Fxaml-basics","01.csharp\u002F12.desktop-ui\u002F04.xaml-basics",{"title":1391,"path":1392,"stem":1393},"Fluent UI у WPF — сучасний дизайн Windows 11","\u002Fcsharp\u002Fdesktop-ui\u002F04a.wpf-fluent-ui","01.csharp\u002F12.desktop-ui\u002F04a.wpf-fluent-ui",{"title":1395,"path":1396,"stem":1397},"WPF UI — сучасна бібліотека Fluent контролів","\u002Fcsharp\u002Fdesktop-ui\u002F04b.wpf-ui-library","01.csharp\u002F12.desktop-ui\u002F04b.wpf-ui-library",{"title":1399,"path":1400,"stem":1401},"HandyControl — велика бібліотека UI контролів для WPF","\u002Fcsharp\u002Fdesktop-ui\u002F04c.handycontrol-library","01.csharp\u002F12.desktop-ui\u002F04c.handycontrol-library",{"title":1403,"path":1404,"stem":1405},"Простори імен та ресурси XAML","\u002Fcsharp\u002Fdesktop-ui\u002Fxaml-namespaces-resources","01.csharp\u002F12.desktop-ui\u002F05.xaml-namespaces-resources",{"title":1407,"path":1408,"stem":1409},"XAML в Avalonia: ключові відмінності від WPF","\u002Fcsharp\u002Fdesktop-ui\u002F05a.avalonia-xaml-differences","01.csharp\u002F12.desktop-ui\u002F05a.avalonia-xaml-differences",{"title":1411,"path":1412,"stem":1413},"Розширення розмітки XAML (Markup Extensions)","\u002Fcsharp\u002Fdesktop-ui\u002Fxaml-markup-extensions","01.csharp\u002F12.desktop-ui\u002F06.xaml-markup-extensions",{"title":1415,"path":1416,"stem":1417},"Панелі Layout: StackPanel, WrapPanel, DockPanel","\u002Fcsharp\u002Fdesktop-ui\u002Flayout-panels-part1","01.csharp\u002F12.desktop-ui\u002F07.layout-panels-part1",{"title":1419,"path":1420,"stem":1421},"Grid, Canvas, UniformGrid","\u002Fcsharp\u002Fdesktop-ui\u002Flayout-panels-part2","01.csharp\u002F12.desktop-ui\u002F07.layout-panels-part2",{"title":1423,"path":1424,"stem":1425},"Просунуті техніки Layout","\u002Fcsharp\u002Fdesktop-ui\u002Flayout-advanced","01.csharp\u002F12.desktop-ui\u002F08.layout-advanced",{"title":1427,"path":1428,"stem":1429},"Адаптивний Layout та найкращі практики","\u002Fcsharp\u002Fdesktop-ui\u002Flayout-responsive","01.csharp\u002F12.desktop-ui\u002F09.layout-responsive",{"title":1431,"path":1432,"stem":1433},"Layout в Avalonia: відмінності та нові можливості","\u002Fcsharp\u002Fdesktop-ui\u002F09a.layout-avalonia","01.csharp\u002F12.desktop-ui\u002F09a.layout-avalonia",{"title":1435,"path":1436,"stem":1437},"Button, Image, ProgressBar та інші базові контроли","\u002Fcsharp\u002Fdesktop-ui\u002Fbasic-controls","01.csharp\u002F12.desktop-ui\u002F10.basic-controls",{"title":1439,"path":1440,"stem":1441},"Контроли в Avalonia: відмінності від WPF","\u002Fcsharp\u002Fdesktop-ui\u002F10a.controls-avalonia","01.csharp\u002F12.desktop-ui\u002F10a.controls-avalonia",{"title":1443,"path":1444,"stem":1445},"Текстові контроли — TextBlock, TextBox, RichTextBox","\u002Fcsharp\u002Fdesktop-ui\u002Ftext-controls","01.csharp\u002F12.desktop-ui\u002F11.text-controls",{"title":1447,"path":1448,"stem":1449},"Контроли вибору — CheckBox, RadioButton, ComboBox, ListBox, DatePicker","\u002Fcsharp\u002Fdesktop-ui\u002Fselection-controls","01.csharp\u002F12.desktop-ui\u002F12.selection-controls",{"title":1451,"path":1452,"stem":1453},"Content Model — GroupBox, Expander, TabControl, StatusBar","\u002Fcsharp\u002Fdesktop-ui\u002Fcontent-controls","01.csharp\u002F12.desktop-ui\u002F13.content-controls",{"title":1455,"path":1456,"stem":1457},"UI\u002FUX принципи десктопних застосунків","\u002Fcsharp\u002Fdesktop-ui\u002F13a.ui-ux-principles","01.csharp\u002F12.desktop-ui\u002F13a.ui-ux-principles",{"title":1459,"path":1460,"stem":1461},"Dependency Properties — Концепція та Value Resolution","\u002Fcsharp\u002Fdesktop-ui\u002Fdependency-properties-part1","01.csharp\u002F12.desktop-ui\u002F14.dependency-properties-part1",{"title":1463,"path":1464,"stem":1465},"Avalonia Property System — StyledProperty та DirectProperty","\u002Fcsharp\u002Fdesktop-ui\u002F14a.avalonia-property-system","01.csharp\u002F12.desktop-ui\u002F14a.avalonia-property-system",{"title":1467,"path":1468,"stem":1469},"Attached Properties — Властивості без меж","\u002Fcsharp\u002Fdesktop-ui\u002Fattached-properties","01.csharp\u002F12.desktop-ui\u002F15.attached-properties",{"title":1471,"path":1472,"stem":1473},"Routed Events — Маршрутизація подій у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Frouted-events","01.csharp\u002F12.desktop-ui\u002F16.routed-events",{"title":1475,"path":1476,"stem":1477},"Data Binding — Від Code-Behind до Декларативності","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-binding-basics-part1","01.csharp\u002F12.desktop-ui\u002F17.data-binding-basics-part1",{"title":1479,"path":1480,"stem":1481},"INotifyPropertyChanged — Живе оновлення UI","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-binding-basics-part2","01.csharp\u002F12.desktop-ui\u002F17.data-binding-basics-part2",{"title":1483,"path":1484,"stem":1485},"Compiled Bindings в Avalonia — Безпека на етапі компіляції","\u002Fcsharp\u002Fdesktop-ui\u002F17a.avalonia-compiled-bindings","01.csharp\u002F12.desktop-ui\u002F17a.avalonia-compiled-bindings",{"title":1487,"path":1488,"stem":1489},"Просунутий Data Binding — ElementName, RelativeSource, MultiBinding","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-binding-advanced","01.csharp\u002F12.desktop-ui\u002F18.data-binding-advanced",{"title":1491,"path":1492,"stem":1493},"Value Converters — Перетворення типів даних у Data Binding","\u002Fcsharp\u002Fdesktop-ui\u002Fvalue-converters","01.csharp\u002F12.desktop-ui\u002F19.value-converters",{"title":1495,"path":1496,"stem":1497},"Data Templates — Візуалізація об'єктів у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-templates","01.csharp\u002F12.desktop-ui\u002F20.data-templates",{"title":1499,"path":1500,"stem":1501},"Collections Binding Part 1 — ObservableCollection та ItemsControl","\u002Fcsharp\u002Fdesktop-ui\u002Fcollections-binding-part1","01.csharp\u002F12.desktop-ui\u002F21.collections-binding-part1",{"title":1503,"path":1504,"stem":1505},"Collections Binding Part 2 — ICollectionView, Filtering, Sorting та Virtualization","\u002Fcsharp\u002Fdesktop-ui\u002Fcollections-binding-part2","01.csharp\u002F12.desktop-ui\u002F21.collections-binding-part2",{"title":1507,"path":1508,"stem":1509},"MVVM Pattern — Від Spaghetti Code до архітектури","\u002Fcsharp\u002Fdesktop-ui\u002Fmvvm-pattern","01.csharp\u002F12.desktop-ui\u002F22.mvvm-pattern",{"title":1511,"path":1512,"stem":1513},"ViewModel Implementation — Від BaseViewModel до валідації","\u002Fcsharp\u002Fdesktop-ui\u002Fviewmodel-implementation","01.csharp\u002F12.desktop-ui\u002F23.viewmodel-implementation",{"title":1515,"path":1516,"stem":1517},"Commands — Від event handlers до декларативних команд","\u002Fcsharp\u002Fdesktop-ui\u002Fcommands","01.csharp\u002F12.desktop-ui\u002F24.commands",{"title":1519,"path":1520,"stem":1521},"MVVM Toolkit — MVVM без boilerplate через Source Generators","\u002Fcsharp\u002Fdesktop-ui\u002Fmvvm-toolkit","01.csharp\u002F12.desktop-ui\u002F25.mvvm-toolkit",{"title":1523,"path":1524,"stem":1525},"Messenger Pattern — Комунікація між ViewModel без прямих посилань","\u002Fcsharp\u002Fdesktop-ui\u002Fmessenger-pattern","01.csharp\u002F12.desktop-ui\u002F26.messenger-pattern",{"title":1527,"path":1528,"stem":1529},"Стилі WPF — CSS для десктопу","\u002Fcsharp\u002Fdesktop-ui\u002Fstyles-basics","01.csharp\u002F12.desktop-ui\u002F27.styles-basics",{"title":1531,"path":1532,"stem":1533},"CSS-like стилі Avalonia","\u002Fcsharp\u002Fdesktop-ui\u002F27a.avalonia-css-styling","01.csharp\u002F12.desktop-ui\u002F27a.avalonia-css-styling",{"title":1535,"path":1536,"stem":1537},"Control Templates — Частина 1. Концепція та TemplateBinding","\u002Fcsharp\u002Fdesktop-ui\u002Fcontrol-templates-part1","01.csharp\u002F12.desktop-ui\u002F28.control-templates-part1",{"title":1539,"path":1540,"stem":1541},"Control Templates — Частина 2. Named Parts та ContentPresenter","\u002Fcsharp\u002Fdesktop-ui\u002Fcontrol-templates-part2","01.csharp\u002F12.desktop-ui\u002F28.control-templates-part2",{"title":1543,"path":1544,"stem":1545},"Control Themes в Avalonia — нова ера стилізації","\u002Fcsharp\u002Fdesktop-ui\u002F28a.avalonia-control-themes","01.csharp\u002F12.desktop-ui\u002F28a.avalonia-control-themes",{"title":1547,"path":1548,"stem":1549},"Triggers та Visual State Manager у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Ftriggers-visual-states","01.csharp\u002F12.desktop-ui\u002F29.triggers-visual-states",{"title":1551,"path":1552,"stem":1553},"Pseudo-classes в Avalonia — замість WPF Triggers","\u002Fcsharp\u002Fdesktop-ui\u002F29a.avalonia-pseudo-classes","01.csharp\u002F12.desktop-ui\u002F29a.avalonia-pseudo-classes",{"title":1555,"path":1556,"stem":1557},"Теми та ресурсні словники у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fresources-themes","01.csharp\u002F12.desktop-ui\u002F30.resources-themes",{"title":1559,"path":1560,"stem":1561},"Avalonia Themes — Fluent Design та система тематизації","\u002Fcsharp\u002Fdesktop-ui\u002F30a.avalonia-themes-fluent","01.csharp\u002F12.desktop-ui\u002F30a.avalonia-themes-fluent",{"title":1563,"path":1564,"stem":1565},"Контроли колекцій — глибоке занурення","\u002Fcsharp\u002Fdesktop-ui\u002Fcollection-controls","01.csharp\u002F12.desktop-ui\u002F31.collection-controls",{"title":1567,"path":1568,"stem":1569},"DataGrid — колонки та базове відображення","\u002Fcsharp\u002Fdesktop-ui\u002Fdatagrid-part1","01.csharp\u002F12.desktop-ui\u002F32.datagrid-part1",{"title":1571,"path":1572,"stem":1573},"DataGrid — сортування, фільтрація, редагування","\u002Fcsharp\u002Fdesktop-ui\u002Fdatagrid-part2","01.csharp\u002F12.desktop-ui\u002F32.datagrid-part2",{"title":1575,"path":1576,"stem":1577},"TreeView та GridView","\u002Fcsharp\u002Fdesktop-ui\u002Ftreeview-listview","01.csharp\u002F12.desktop-ui\u002F33.treeview-listview",{"title":1579,"path":1580,"stem":1581},"Меню, Toolbar, ContextMenu, StatusBar","\u002Fcsharp\u002Fdesktop-ui\u002Fmenus-toolbars","01.csharp\u002F12.desktop-ui\u002F34.menus-toolbars",{"title":1583,"path":1584,"stem":1585},"Навігація та керування вікнами. Частина 1: вікна та сторінки","\u002Fcsharp\u002Fdesktop-ui\u002Fnavigation-windows-part1","01.csharp\u002F12.desktop-ui\u002F35.navigation-windows-part1",{"title":1587,"path":1588,"stem":1589},"Навігація та керування вікнами. Частина 2: MVVM-навігація","\u002Fcsharp\u002Fdesktop-ui\u002Fnavigation-windows-part2","01.csharp\u002F12.desktop-ui\u002F35.navigation-windows-part2",{"title":1591,"path":1592,"stem":1593},"Avalonia — Навігація та діалоги","\u002Fcsharp\u002Fdesktop-ui\u002F35a.avalonia-navigation-dialogs","01.csharp\u002F12.desktop-ui\u002F35a.avalonia-navigation-dialogs",{"title":1595,"path":1596,"stem":1597},"Діалоги та File Pickers у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fdialogs-file-pickers","01.csharp\u002F12.desktop-ui\u002F36.dialogs-file-pickers",{"title":1599,"path":1600,"stem":1601},"UserControl: компонентний підхід у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fuser-controls","01.csharp\u002F12.desktop-ui\u002F37.user-controls",{"title":1603,"path":1604,"stem":1605},"Custom Controls: Lookless Controls у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fcustom-controls","01.csharp\u002F12.desktop-ui\u002F38.custom-controls",{"title":1607,"path":1608,"stem":1609},"Avalonia TemplatedControl — Lookless Controls","\u002Fcsharp\u002Fdesktop-ui\u002F38a.avalonia-templated-controls","01.csharp\u002F12.desktop-ui\u002F38a.avalonia-templated-controls",{"title":1611,"path":1612,"stem":1613},"Анімації у WPF: Storyboard та Easing Functions","\u002Fcsharp\u002Fdesktop-ui\u002Fanimations-transitions","01.csharp\u002F12.desktop-ui\u002F39.animations-transitions",{"title":1615,"path":1616,"stem":1617},"Анімації в Avalonia","\u002Fcsharp\u002Fdesktop-ui\u002F39a.avalonia-animations","01.csharp\u002F12.desktop-ui\u002F39a.avalonia-animations",{"title":1619,"path":1620,"stem":1621},"2D Графіка та Мультимедіа у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fmedia-graphics","01.csharp\u002F12.desktop-ui\u002F40.media-graphics",{"title":1623,"path":1624,"stem":1625},"Dependency Injection у WPF та Avalonia","\u002Fcsharp\u002Fdesktop-ui\u002Fdi-integration","01.csharp\u002F12.desktop-ui\u002F41.di-integration",{"title":1627,"path":1628,"stem":1629},"SQLite та EF Core у десктопних додатках","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-persistence-part1","01.csharp\u002F12.desktop-ui\u002F42.data-persistence-part1",{"title":1631,"path":1632,"stem":1633},"Repository Pattern та Unit of Work","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-persistence-part2","01.csharp\u002F12.desktop-ui\u002F43.data-persistence-part2",{"title":1635,"path":1636,"stem":1637},"Тестування ViewModels","\u002Fcsharp\u002Fdesktop-ui\u002Fviewmodel-testing","01.csharp\u002F12.desktop-ui\u002F44.viewmodel-testing",{"title":1639,"path":1640,"stem":1641},"Avalonia Headless Testing — тестування UI без вікон","\u002Fcsharp\u002Fdesktop-ui\u002F44a.avalonia-headless-testing","01.csharp\u002F12.desktop-ui\u002F44a.avalonia-headless-testing",{"title":1643,"path":1644,"stem":1645},"Кросплатформна розробка з Avalonia","\u002Fcsharp\u002Fdesktop-ui\u002Favalonia-cross-platform","01.csharp\u002F12.desktop-ui\u002F45.avalonia-cross-platform",{"title":1647,"path":1648,"stem":1649},"Пакування та розгортання Avalonia додатків","\u002Fcsharp\u002Fdesktop-ui\u002Favalonia-packaging-deployment","01.csharp\u002F12.desktop-ui\u002F46.avalonia-packaging-deployment",{"title":1651,"path":1652,"stem":1653},"Розгортання WPF застосунків","\u002Fcsharp\u002Fdesktop-ui\u002Fwpf-packaging-deployment","01.csharp\u002F12.desktop-ui\u002F47.wpf-packaging-deployment",{"title":1655,"icon":658,"path":1656,"stem":1657,"children":1658,"page":59},"Network Programming","\u002Fcsharp\u002Fnetwork-programming","01.csharp\u002F13.network-programming",[1659,1663,1667,1671,1675,1679,1683,1687,1691,1695,1699],{"title":1660,"path":1661,"stem":1662},"Основи комп'ютерних мереж","\u002Fcsharp\u002Fnetwork-programming\u002Ffoundations","01.csharp\u002F13.network-programming\u002F01.foundations",{"title":1664,"path":1665,"stem":1666},"Модель OSI та стек TCP\u002FIP","\u002Fcsharp\u002Fnetwork-programming\u002Fosi-model","01.csharp\u002F13.network-programming\u002F02.osi-model",{"title":1668,"path":1669,"stem":1670},"IP-протокол та адресація","\u002Fcsharp\u002Fnetwork-programming\u002Fip-addressing","01.csharp\u002F13.network-programming\u002F03.ip-addressing",{"title":1672,"path":1673,"stem":1674},"UDP — протокол без з'єднання","\u002Fcsharp\u002Fnetwork-programming\u002Fudp","01.csharp\u002F13.network-programming\u002F05.udp",{"title":1676,"path":1677,"stem":1678},"UDP Broadcast та Multicast","\u002Fcsharp\u002Fnetwork-programming\u002Fudp-broadcast-multicast","01.csharp\u002F13.network-programming\u002F06.udp-broadcast-multicast",{"title":1680,"path":1681,"stem":1682},"HTTP — протокол вебу","\u002Fcsharp\u002Fnetwork-programming\u002Fhttp-fundamentals","01.csharp\u002F13.network-programming\u002F07.http-fundamentals",{"title":1684,"path":1685,"stem":1686},"HttpListener — вбудований HTTP-сервер .NET","\u002Fcsharp\u002Fnetwork-programming\u002F07a.http-listener","01.csharp\u002F13.network-programming\u002F07a.http-listener",{"title":1688,"path":1689,"stem":1690},"HTTP Advanced — cookies, аутентифікація та HTTPS","\u002Fcsharp\u002Fnetwork-programming\u002Fhttp-advanced","01.csharp\u002F13.network-programming\u002F08.http-advanced",{"title":1692,"path":1693,"stem":1694},"SMTP та протоколи електронної пошти","\u002Fcsharp\u002Fnetwork-programming\u002Fsmtp","01.csharp\u002F13.network-programming\u002F09.smtp",{"title":1696,"path":1697,"stem":1698},"WebSocket — повнодуплексний протокол реального часу","\u002Fcsharp\u002Fnetwork-programming\u002Fwebsockets","01.csharp\u002F13.network-programming\u002F10.websockets",{"title":1700,"path":1701,"stem":1702},"TLS\u002FSSL — криптографічний захист мережевих з'єднань","\u002Fcsharp\u002Fnetwork-programming\u002Ftls-ssl","01.csharp\u002F13.network-programming\u002F11.tls-ssl",{"title":1704,"path":1705,"stem":1706},"C# & .NET: The Ultimate Roadmap","\u002Fcsharp\u002Froadmap","01.csharp\u002Froadmap",{"title":1708,"icon":1709,"path":1710,"stem":1711,"children":1712,"page":59},"C++","i-devicon-cplusplus","\u002Fcpp","02.cpp",[1713,1717,1721,1725,1729,1733,1737,1741,1745,1748,1752,1756,1760,1764,1768,1772,1776,1780,1784,1788,1792,1796,1800,1804,1808,1812,1816,1820,1824,1828,1832,1836,1840,1844,1848,1852,1856,1860,1864,1868,1872,1876,1880,1884,1888,1892,1896,1900,1904,1908,1912,1916,1920,1924,1928,1932,1936,1940,1944,1948,1952,1956,1960,1964,1968,1972,1976,1980,1984,1988,1992,1996,2000,2004,2008,2012,2016,2020,2024,2028,2032,2036,2040,2044,2048,2052,2056,2060,2064,2068,2072,2076,2080],{"title":1714,"path":1715,"stem":1716},"Вступ у програмування та алгоритми","\u002Fcpp\u002Fintro-algorithms","02.cpp\u002F01.intro-algorithms",{"title":1718,"path":1719,"stem":1720},"Code Style: угоди про оформлення коду","\u002Fcpp\u002Fcode-style","02.cpp\u002F02.code-style",{"title":1722,"path":1723,"stem":1724},"Середовище розробки та перший проєкт","\u002Fcpp\u002Fide-setup","02.cpp\u002F03.ide-setup",{"title":1726,"path":1727,"stem":1728},"Вивід даних на екран","\u002Fcpp\u002Fdata-output","02.cpp\u002F04.data-output",{"title":1730,"path":1731,"stem":1732},"Типи даних, змінні та константи","\u002Fcpp\u002Fdata-types-variables","02.cpp\u002F05.data-types-variables",{"title":1734,"path":1735,"stem":1736},"Ввід даних з клавіатури","\u002Fcpp\u002Fdata-input","02.cpp\u002F06.data-input",{"title":1738,"path":1739,"stem":1740},"Оператори, перетворення типів та логічні операції","\u002Fcpp\u002Foperators-type-conversion","02.cpp\u002F07.operators-type-conversion",{"title":1742,"path":1743,"stem":1744},"Цикли","\u002Fcpp\u002Floops","02.cpp\u002F08.loops",{"title":32,"path":1746,"stem":1747},"\u002Fcpp\u002Farrays","02.cpp\u002F09.arrays",{"title":1749,"path":1750,"stem":1751},"Алгоритми сортування та аналіз складності","\u002Fcpp\u002Fsorting","02.cpp\u002F10.sorting",{"title":1753,"path":1754,"stem":1755},"Алгоритми пошуку","\u002Fcpp\u002Fsearching","02.cpp\u002F11.searching",{"title":1757,"path":1758,"stem":1759},"Функції: основи","\u002Fcpp\u002Ffunctions-basics","02.cpp\u002F12.functions-basics",{"title":1761,"path":1762,"stem":1763},"Функції: прототипи, область видимості та додаткові можливості","\u002Fcpp\u002Ffunctions-scope","02.cpp\u002F13.functions-scope",{"title":1765,"path":1766,"stem":1767},"Функції: перевантаження та шаблони","\u002Fcpp\u002Ffunctions-overloading-templates","02.cpp\u002F14.functions-overloading-templates",{"title":1769,"path":1770,"stem":1771},"Вказівники: основи","\u002Fcpp\u002Fpointers-basics","02.cpp\u002F15.pointers-basics",{"title":1773,"path":1774,"stem":1775},"Посилання (References)","\u002Fcpp\u002Freferences","02.cpp\u002F16.references",{"title":1777,"path":1778,"stem":1779},"Вказівники, const і масиви","\u002Fcpp\u002Fpointers-const-arrays","02.cpp\u002F17.pointers-const-arrays",{"title":1781,"path":1782,"stem":1783},"Адресна арифметика","\u002Fcpp\u002Fpointer-arithmetic","02.cpp\u002F18.pointer-arithmetic",{"title":1785,"path":1786,"stem":1787},"Динамічна пам'ять","\u002Fcpp\u002Fdynamic-memory","02.cpp\u002F19.dynamic-memory",{"title":1789,"path":1790,"stem":1791},"Вказівники типу void","\u002Fcpp\u002Fvoid-pointers","02.cpp\u002F20.void-pointers",{"title":1793,"path":1794,"stem":1795},"Вказівники на вказівники","\u002Fcpp\u002Fpointers-to-pointers","02.cpp\u002F21.pointers-to-pointers",{"title":1797,"path":1798,"stem":1799},"Оператор доступу до членів через вказівник (->)","\u002Fcpp\u002Fmember-access-operator","02.cpp\u002F22.member-access-operator",{"title":1801,"path":1802,"stem":1803},"Цикл for-each (Range-based for)","\u002Fcpp\u002Fforeach-loop","02.cpp\u002F23.foreach-loop",{"title":1805,"path":1806,"stem":1807},"Вказівники на функції","\u002Fcpp\u002Ffunction-pointers","02.cpp\u002F24.function-pointers",{"title":1809,"path":1810,"stem":1811},"Лямбда-вирази","\u002Fcpp\u002Flambdas","02.cpp\u002F25.lambdas",{"title":1813,"path":1814,"stem":1815},"Лямбда-захоплення","\u002Fcpp\u002Flambda-captures","02.cpp\u002F26.lambda-captures",{"title":1817,"path":1818,"stem":1819},"Еліпсис","\u002Fcpp\u002Fellipsis","02.cpp\u002F27.ellipsis",{"title":1821,"path":1822,"stem":1823},"Безпечні альтернативи еліпсису","\u002Fcpp\u002F27a.ellipsis","02.cpp\u002F27a.ellipsis",{"title":1825,"path":1826,"stem":1827},"Аргументи командного рядка","\u002Fcpp\u002Fcommand-line-arguments","02.cpp\u002F28.command-line-arguments",{"title":1829,"path":1830,"stem":1831},"Перерахування (enum)","\u002Fcpp\u002Fenum","02.cpp\u002F29.enum",{"title":1833,"path":1834,"stem":1835},"Класи-перерахування (enum class)","\u002Fcpp\u002Fenum-class","02.cpp\u002F30.enum-class",{"title":1837,"path":1838,"stem":1839},"Псевдоніми типів (typedef і using)","\u002Fcpp\u002Ftype-aliases","02.cpp\u002F31.type-aliases",{"title":1841,"path":1842,"stem":1843},"Системи числення та двійкова арифметика","\u002Fcpp\u002Fnumber-systems","02.cpp\u002F32.number-systems",{"title":1845,"path":1846,"stem":1847},"Структури (struct): агрегування даних","\u002Fcpp\u002Fstruct","02.cpp\u002F33.struct",{"title":1849,"path":1850,"stem":1851},"Структури у функціях","\u002Fcpp\u002Fstruct-functions","02.cpp\u002F34.struct-functions",{"title":1853,"path":1854,"stem":1855},"Масиви структур і вкладені структури","\u002Fcpp\u002Fstruct-arrays","02.cpp\u002F35.struct-arrays",{"title":1857,"path":1858,"stem":1859},"Патерни struct та межі застосування","\u002Fcpp\u002Fstruct-patterns","02.cpp\u002F36.struct-patterns",{"title":1861,"path":1862,"stem":1863},"Символи та таблиця ASCII","\u002Fcpp\u002Fascii-characters","02.cpp\u002F37.ascii-characters",{"title":1865,"path":1866,"stem":1867},"Unicode та кодування UTF","\u002Fcpp\u002Funicode-utf","02.cpp\u002F38.unicode-utf",{"title":1869,"path":1870,"stem":1871},"C-style рядки","\u002Fcpp\u002Fc-strings","02.cpp\u002F39.c-strings",{"title":1873,"path":1874,"stem":1875},"Вступ до std::string","\u002Fcpp\u002Fstd-string-intro","02.cpp\u002F40.std-string-intro",{"title":1877,"path":1878,"stem":1879},"Довжина, ємність та доступ до символів std::string","\u002Fcpp\u002Fstd-string-capacity-access","02.cpp\u002F41.std-string-capacity-access",{"title":1881,"path":1882,"stem":1883},"Модифікація std::string: присвоювання, додавання, вставка, видалення та заміна","\u002Fcpp\u002Fstd-string-modification","02.cpp\u002F42.std-string-modification",{"title":1885,"path":1886,"stem":1887},"Пошук у std::string: find, npos та практичні патерни","\u002Fcpp\u002Fstd-string-search","02.cpp\u002F43.std-string-search",{"title":1889,"path":1890,"stem":1891},"std::string_view: невласницький погляд на рядок без копіювання","\u002Fcpp\u002Fstd-string-view","02.cpp\u002F44.std-string-view",{"title":1893,"path":1894,"stem":1895},"Об'єднання (union): один блок пам'яті, кілька інтерпретацій","\u002Fcpp\u002Funion","02.cpp\u002F45.union",{"title":1897,"path":1898,"stem":1899},"Організація коду: файли, препроцесор, простори імен","\u002Fcpp\u002Fmultifile-programs","02.cpp\u002F46.multifile-programs",{"title":1901,"path":1902,"stem":1903},"Робота з файлами: C-стиль (stdio.h)","\u002Fcpp\u002Fc-style-files","02.cpp\u002F47.c-style-files",{"title":1905,"path":1906,"stem":1907},"Робота з файлами: C++-стиль (fstream)","\u002Fcpp\u002Fcpp-style-files","02.cpp\u002F48.cpp-style-files",{"title":1909,"path":1910,"stem":1911},"Введення в ООП: від процедур до об'єктів","\u002Fcpp\u002Foop-intro","02.cpp\u002F49.oop-intro",{"title":1913,"path":1914,"stem":1915},"Класи, об'єкти та методи","\u002Fcpp\u002Fclasses-objects-methods","02.cpp\u002F50.classes-objects-methods",{"title":1917,"path":1918,"stem":1919},"Специфікатори доступу та інкапсуляція","\u002Fcpp\u002Faccess-specifiers-encapsulation","02.cpp\u002F51.access-specifiers-encapsulation",{"title":1921,"path":1922,"stem":1923},"Конструктори: гарантована ініціалізація об'єктів","\u002Fcpp\u002Fconstructors","02.cpp\u002F52.constructors",{"title":1925,"path":1926,"stem":1927},"Списки ініціалізації та делегуючі конструктори","\u002Fcpp\u002Finit-lists-delegating","02.cpp\u002F53.init-lists-delegating",{"title":1929,"path":1930,"stem":1931},"Деструктори та ідіома RAII","\u002Fcpp\u002Fdestructors-raii","02.cpp\u002F54.destructors-raii",{"title":1933,"path":1934,"stem":1935},"Прихований покажчик this","\u002Fcpp\u002Fthis-pointer","02.cpp\u002F55.this-pointer",{"title":1937,"path":1938,"stem":1939},"Розподіл класу на заголовковий файл та файл реалізації","\u002Fcpp\u002Fclass-header-source","02.cpp\u002F56.class-header-source",{"title":1941,"path":1942,"stem":1943},"Класи та const","\u002Fcpp\u002Fconst-classes","02.cpp\u002F57.const-classes",{"title":1945,"path":1946,"stem":1947},"Статичні члени класу","\u002Fcpp\u002Fstatic-members","02.cpp\u002F58.static-members",{"title":1949,"path":1950,"stem":1951},"Конструктор копіювання та запобігання копіюванню","\u002Fcpp\u002Fcopy-constructor","02.cpp\u002F59.copy-constructor",{"title":1953,"path":1954,"stem":1955},"Дружні функції та класи","\u002Fcpp\u002Ffriend-functions-classes","02.cpp\u002F60.friend-functions-classes",{"title":1957,"path":1958,"stem":1959},"Анонімні об'єкти та вкладені типи","\u002Fcpp\u002Fanonymous-objects-nested-types","02.cpp\u002F61.anonymous-objects-nested-types",{"title":1961,"path":1962,"stem":1963},"Вимірювання часу виконання: RAII-таймер","\u002Fcpp\u002Ftiming-raii-timer","02.cpp\u002F62.timing-raii-timer",{"title":1965,"path":1966,"stem":1967},"Перевантаження операторів: основи та арифметика","\u002Fcpp\u002Foperator-overloading-basics","02.cpp\u002F63.operator-overloading-basics",{"title":1969,"path":1970,"stem":1971},"Перевантаження операторів: методи класу та спеціальні оператори","\u002Fcpp\u002Foperator-overloading-methods","02.cpp\u002F64.operator-overloading-methods",{"title":1973,"path":1974,"stem":1975},"Приведення типів, explicit та delete","\u002Fcpp\u002Ftypecast-explicit-delete","02.cpp\u002F65.typecast-explicit-delete",{"title":1977,"path":1978,"stem":1979},"Глибоке копіювання та оператор присвоювання","\u002Fcpp\u002Fdeep-copy-assignment","02.cpp\u002F66.deep-copy-assignment",{"title":1981,"path":1982,"stem":1983},"Зв'язки між об'єктами: композиція та агрегація","\u002Fcpp\u002Fcomposition-aggregation","02.cpp\u002F67.composition-aggregation",{"title":1985,"path":1986,"stem":1987},"Асоціація та залежність між об","\u002Fcpp\u002Fassociation-dependency","02.cpp\u002F68.association-dependency",{"title":1989,"path":1990,"stem":1991},"Контейнерні класи та `std::initializer_list`","\u002Fcpp\u002Fcontainer-classes-initializer-list","02.cpp\u002F69.container-classes-initializer-list",{"title":1993,"path":1994,"stem":1995},"Вступ до наслідування: базові поняття та відношення «is-a»","\u002Fcpp\u002Finheritance-intro","02.cpp\u002F70.inheritance-intro",{"title":1997,"path":1998,"stem":1999},"Конструктори, деструктори та порядок ініціалізації в ієрархіях","\u002Fcpp\u002Finheritance-constructors-destructors","02.cpp\u002F71.inheritance-constructors-destructors",{"title":2001,"path":2002,"stem":2003},"Специфікатор `protected` та види наслідування","\u002Fcpp\u002Finheritance-access-specifiers","02.cpp\u002F72.inheritance-access-specifiers",{"title":2005,"path":2006,"stem":2007},"Перевизначення методів та приховування імен","\u002Fcpp\u002Fmethod-overriding-hiding","02.cpp\u002F73.method-overriding-hiding",{"title":2009,"path":2010,"stem":2011},"Множинне наслідування та проблема ромба","\u002Fcpp\u002Fmultiple-inheritance-diamond","02.cpp\u002F74.multiple-inheritance-diamond",{"title":2013,"path":2014,"stem":2015},"Вказівники на базовий клас та віртуальні функції","\u002Fcpp\u002Fvirtual-functions-polymorphism","02.cpp\u002F75.virtual-functions-polymorphism",{"title":2017,"path":2018,"stem":2019},"Специфікатори override, final та віртуальні деструктори","\u002Fcpp\u002Foverride-final-virtual-destructors","02.cpp\u002F76.override-final-virtual-destructors",{"title":2021,"path":2022,"stem":2023},"Внутрішні механізми поліморфізму: vtable, vptr та зв'язування","\u002Fcpp\u002Fvirtual-table-binding","02.cpp\u002F77.virtual-table-binding",{"title":2025,"path":2026,"stem":2027},"Абстрактні класи та чисті віртуальні функції","\u002Fcpp\u002Fabstract-classes-interfaces","02.cpp\u002F78.abstract-classes-interfaces",{"title":2029,"path":2030,"stem":2031},"Зрізка об'єктів, віртуальне наслідування та поліморфний вивід","\u002Fcpp\u002Fslicing-virtual-base-io","02.cpp\u002F79.slicing-virtual-base-io",{"title":2033,"path":2034,"stem":2035},"Динамічне приведення типів (`dynamic_cast`) та RTTI","\u002Fcpp\u002Fdynamic-cast-rtti","02.cpp\u002F80.dynamic-cast-rtti",{"title":2037,"path":2038,"stem":2039},"Шаблони функцій: узагальнене програмування","\u002Fcpp\u002Ffunction-templates","02.cpp\u002F81.function-templates",{"title":2041,"path":2042,"stem":2043},"Шаблони класів та NTTP-параметри","\u002Fcpp\u002Fclass-templates-nttp","02.cpp\u002F82.class-templates-nttp",{"title":2045,"path":2046,"stem":2047},"Повна (явна) спеціалізація шаблонів","\u002Fcpp\u002Ffull-template-specialization","02.cpp\u002F83.full-template-specialization",{"title":2049,"path":2050,"stem":2051},"Часткова спеціалізація шаблонів класів","\u002Fcpp\u002Fpartial-template-specialization","02.cpp\u002F84.partial-template-specialization",{"title":2053,"path":2054,"stem":2055},"Механізм винятків: try, catch, throw та розкручування стеку","\u002Fcpp\u002Fexceptions-basics","02.cpp\u002F85.exceptions-basics",{"title":2057,"path":2058,"stem":2059},"Ієрархія std::exception та власні класи винятків","\u002Fcpp\u002Fexception-hierarchy-custom","02.cpp\u002F86.exception-hierarchy-custom",{"title":2061,"path":2062,"stem":2063},"Повторне генерування винятків та функціональний try-блок","\u002Fcpp\u002Frethrow-function-try","02.cpp\u002F87.rethrow-function-try",{"title":2065,"path":2066,"stem":2067},"Безпека винятків, noexcept та деструктори","\u002Fcpp\u002Fsafety-noexcept","02.cpp\u002F88.safety-noexcept",{"title":2069,"path":2070,"stem":2071},"Стаття 89 — Власні структури даних: стек та черга","\u002Fcpp\u002Fcustom-stack-queue","02.cpp\u002F89.custom-stack-queue",{"title":2073,"path":2074,"stem":2075},"Стаття 90 — Власні структури даних: однозв'язаний список","\u002Fcpp\u002Flinked-list","02.cpp\u002F90.linked-list",{"title":2077,"path":2078,"stem":2079},"Стаття 91 — Власні структури даних: бінарне дерево пошуку","\u002Fcpp\u002Fbinary-search-tree","02.cpp\u002F91.binary-search-tree",{"title":2081,"path":2082,"stem":2083},"Стаття 92 — Власні структури даних: хеш-таблиця","\u002Fcpp\u002Fhash-table","02.cpp\u002F92.hash-table",{"title":2085,"icon":2086,"path":2087,"stem":2088,"children":2089,"page":59},"JavaScript","i-devicon-javascript","\u002Fjavascript","03.javascript",[2090,2116,2170,2192,2496,2534,2552],{"title":2091,"icon":2092,"path":2093,"stem":2094,"children":2095,"page":59},"Events","i-lucide-mouse-pointer-click","\u002Fjavascript\u002Fevents","03.javascript\u002F01.events",[2096,2100,2104,2108,2112],{"title":2097,"path":2098,"stem":2099},"Вступ до подій браузера","\u002Fjavascript\u002Fevents\u002Fintro","03.javascript\u002F01.events\u002F01.intro",{"title":2101,"path":2102,"stem":2103},"Бульбашковий механізм (Bubbling) та занурення (Capturing)","\u002Fjavascript\u002Fevents\u002Fbubbling-capturing","03.javascript\u002F01.events\u002F02.bubbling-capturing",{"title":2105,"path":2106,"stem":2107},"Делегування подій (Event Delegation)","\u002Fjavascript\u002Fevents\u002Fdelegate-events","03.javascript\u002F01.events\u002F03.delegate-events",{"title":2109,"path":2110,"stem":2111},"Типові дії браузера та preventDefault()","\u002Fjavascript\u002Fevents\u002Fprevent-default","03.javascript\u002F01.events\u002F04.prevent-default",{"title":2113,"path":2114,"stem":2115},"Запуск користувацьких подій (Custom Events)","\u002Fjavascript\u002Fevents\u002Fcustom-events","03.javascript\u002F01.events\u002F05.custom-events",{"title":2117,"icon":2118,"path":2119,"stem":2120,"children":2121,"page":59},"Network","i-lucide-globe","\u002Fjavascript\u002Fnetwork","03.javascript\u002F02.network",[2122,2126,2130,2134,2138,2142,2146,2150,2154,2158,2162,2166],{"title":2123,"path":2124,"stem":2125},"Fetch API - Сучасний підхід до HTTP-запитів","\u002Fjavascript\u002Fnetwork\u002F01-fetch-api","03.javascript\u002F02.network\u002F01-fetch-api",{"title":2127,"path":2128,"stem":2129},"FormData - Робота з формами та файлами","\u002Fjavascript\u002Fnetwork\u002F02-formdata","03.javascript\u002F02.network\u002F02-formdata",{"title":2131,"path":2132,"stem":2133},"Відстеження прогресу завантаження","\u002Fjavascript\u002Fnetwork\u002F03-download-progress","03.javascript\u002F02.network\u002F03-download-progress",{"title":2135,"path":2136,"stem":2137},"Переривання fetch-запитів","\u002Fjavascript\u002Fnetwork\u002F04-abort-requests","03.javascript\u002F02.network\u002F04-abort-requests",{"title":2139,"path":2140,"stem":2141},"CORS - Запити між різними джерелами","\u002Fjavascript\u002Fnetwork\u002F05-cors","03.javascript\u002F02.network\u002F05-cors",{"title":2143,"path":2144,"stem":2145},"Fetch API - Повний довідник опцій","\u002Fjavascript\u002Fnetwork\u002F06-fetch-options","03.javascript\u002F02.network\u002F06-fetch-options",{"title":2147,"path":2148,"stem":2149},"URL Objects - Робота з посиланнями","\u002Fjavascript\u002Fnetwork\u002F07-url-objects","03.javascript\u002F02.network\u002F07-url-objects",{"title":2151,"path":2152,"stem":2153},"XMLHttpRequest - AJAX та низькорівневі запити","\u002Fjavascript\u002Fnetwork\u002F08-xmlhttprequest","03.javascript\u002F02.network\u002F08-xmlhttprequest",{"title":2155,"path":2156,"stem":2157},"Відновлюване завантаження файлів","\u002Fjavascript\u002Fnetwork\u002F09-resumable-upload","03.javascript\u002F02.network\u002F09-resumable-upload",{"title":2159,"path":2160,"stem":2161},"Cookies, document.cookie та світ після \"Cookiepocalypse\"","\u002Fjavascript\u002Fnetwork\u002F10-cookies","03.javascript\u002F02.network\u002F10-cookies",{"title":2163,"path":2164,"stem":2165},"js-cookie: Керування Cookies без Болю","\u002Fjavascript\u002Fnetwork\u002F11-js-cookie","03.javascript\u002F02.network\u002F11-js-cookie",{"title":2167,"path":2168,"stem":2169},"Axios: Потужний HTTP-клієнт для JavaScript","\u002Fjavascript\u002Fnetwork\u002F12-axios","03.javascript\u002F02.network\u002F12-axios",{"title":2171,"icon":2172,"path":2173,"stem":2174,"children":2175,"page":59},"Bom","i-lucide-monitor","\u002Fjavascript\u002Fbom","03.javascript\u002F03.bom",[2176,2180,2184,2188],{"title":2177,"path":2178,"stem":2179},"LocalStorage, SessionStorage та patterns збереження даних","\u002Fjavascript\u002Fbom\u002F01-localstorage","03.javascript\u002F03.bom\u002F01-localstorage",{"title":2181,"path":2182,"stem":2183},"Location Object - Керування адресою сторінки","\u002Fjavascript\u002Fbom\u002F02-location-object","03.javascript\u002F03.bom\u002F02-location-object",{"title":2185,"path":2186,"stem":2187},"History API - Керування історією браузера","\u002Fjavascript\u002Fbom\u002F03-history-api","03.javascript\u002F03.bom\u002F03-history-api",{"title":2189,"path":2190,"stem":2191},"Navigator Object - Ідентифікація та Можливості Пристрою","\u002Fjavascript\u002Fbom\u002F04-navigator-object","03.javascript\u002F03.bom\u002F04-navigator-object",{"title":2193,"icon":2194,"path":2195,"stem":2196,"children":2197},"React","i-devicon-react","\u002Fjavascript\u002Freact","03.javascript\u002F04.react\u002Findex",[2198,2199,2203,2207,2211,2215,2278,2313,2465],{"title":2193,"path":2195,"stem":2196},{"title":2200,"path":2201,"stem":2202},"Робота з Формами в React","\u002Fjavascript\u002Freact\u002Freact-forms","03.javascript\u002F04.react\u002F01.react-forms",{"title":2204,"path":2205,"stem":2206},"React Hook Form: Професійна Робота з Формами","\u002Fjavascript\u002Freact\u002Freact-hook-form","03.javascript\u002F04.react\u002F02.react-hook-form",{"title":2208,"path":2209,"stem":2210},"React Hook Form: Глибоке Розуміння Архітектури та Оптимізації","\u002Fjavascript\u002Freact\u002Freact-hook-form-new","03.javascript\u002F04.react\u002F02.react-hook-form-new",{"title":2212,"path":2213,"stem":2214},"Axios та React: Професійна Архітектура Запитів","\u002Fjavascript\u002Freact\u002Fdata-fetching-axios","03.javascript\u002F04.react\u002F03.data-fetching-axios",{"title":2216,"icon":132,"path":2217,"stem":2218,"children":2219},"Tanstack Query","\u002Fjavascript\u002Freact\u002Ftanstack-query","03.javascript\u002F04.react\u002F04.tanstack-query\u002Findex",[2220,2222,2226,2230,2234,2238,2242,2246,2250,2254,2258,2262,2266,2270,2274],{"title":2221,"path":2217,"stem":2218},"TanStack Query: Майстерність Керування Станом Сервера",{"title":2223,"path":2224,"stem":2225},"Парадигма Server State: Чому useEffect недостатньо","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fserver-state-paradigm","03.javascript\u002F04.react\u002F04.tanstack-query\u002F01.server-state-paradigm",{"title":2227,"path":2228,"stem":2229},"Встановлення та Налаштування: Фундамент","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Finstallation-and-devtools","03.javascript\u002F04.react\u002F04.tanstack-query\u002F02.installation-and-devtools",{"title":2231,"path":2232,"stem":2233},"Основи Запитів та Магія Ключів","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fquery-basics-and-keys","03.javascript\u002F04.react\u002F04.tanstack-query\u002F03.query-basics-and-keys",{"title":2235,"path":2236,"stem":2237},"Синхронізація Даних: Життєвий Цикл Запиту","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fdata-synchronization","03.javascript\u002F04.react\u002F04.tanstack-query\u002F04.data-synchronization",{"title":2239,"path":2240,"stem":2241},"Мутації та Інвалідація: Зміна Даних","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fmutations-and-invalidation","03.javascript\u002F04.react\u002F04.tanstack-query\u002F05.mutations-and-invalidation",{"title":2243,"path":2244,"stem":2245},"Оптимістичні Оновлення: Швидше за Світло","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Foptimistic-updates","03.javascript\u002F04.react\u002F04.tanstack-query\u002F06.optimistic-updates",{"title":2247,"path":2248,"stem":2249},"Пагінація та Infinite Scroll","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fpagination-and-load-more","03.javascript\u002F04.react\u002F04.tanstack-query\u002F07.pagination-and-load-more",{"title":2251,"path":2252,"stem":2253},"Просунуті Патерни та Оптимізація","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fadvanced-patterns","03.javascript\u002F04.react\u002F04.tanstack-query\u002F08.advanced-patterns",{"title":2255,"path":2256,"stem":2257},"Архітектура та Best Practices","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Farchitecture-and-best-practices","03.javascript\u002F04.react\u002F04.tanstack-query\u002F09.architecture-and-best-practices",{"title":2259,"path":2260,"stem":2261},"Server-Side Rendering (SSR) та Гідратація","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fserver-side-rendering","03.javascript\u002F04.react\u002F04.tanstack-query\u002F10.server-side-rendering",{"title":2263,"path":2264,"stem":2265},"Стратегії Тестування","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Ftesting-strategies","03.javascript\u002F04.react\u002F04.tanstack-query\u002F11.testing-strategies",{"title":2267,"path":2268,"stem":2269},"Аутентифікація та Обробка Помилок","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fauthentication-and-errors","03.javascript\u002F04.react\u002F04.tanstack-query\u002F12.authentication-and-errors",{"title":2271,"path":2272,"stem":2273},"React Suspense та Майбутнє","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Freact-suspense","03.javascript\u002F04.react\u002F04.tanstack-query\u002F13.react-suspense",{"title":2275,"path":2276,"stem":2277},"Глибоке Занурення в Продуктивність","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fperformance-deep-dive","03.javascript\u002F04.react\u002F04.tanstack-query\u002F14.performance-deep-dive",{"title":2279,"icon":2194,"path":2280,"stem":2281,"children":2282},"React Router","\u002Fjavascript\u002Freact\u002Freact-router","03.javascript\u002F04.react\u002F05.react-router\u002Findex",[2283,2285,2289,2293,2297,2301,2305,2309],{"title":2284,"path":2280,"stem":2281},"React Router: Навігаційна система сучасного вебу",{"title":2286,"path":2287,"stem":2288},"Налаштування та Базовий Роутинг","\u002Fjavascript\u002Freact\u002Freact-router\u002Fsetup-and-basic-routing","03.javascript\u002F04.react\u002F05.react-router\u002F01.setup-and-basic-routing",{"title":2290,"path":2291,"stem":2292},"Динамічна Навігація","\u002Fjavascript\u002Freact\u002Freact-router\u002Fnavigation-and-links","03.javascript\u002F04.react\u002F05.react-router\u002F02.navigation-and-links",{"title":2294,"path":2295,"stem":2296},"Вкладені Маршрути та Макети","\u002Fjavascript\u002Freact\u002Freact-router\u002Fnested-routes-and-layouts","03.javascript\u002F04.react\u002F05.react-router\u002F03.nested-routes-and-layouts",{"title":2298,"path":2299,"stem":2300},"Динамічні Маршрути та Параметри","\u002Fjavascript\u002Freact\u002Freact-router\u002Fdynamic-routing","03.javascript\u002F04.react\u002F05.react-router\u002F04.dynamic-routing",{"title":2302,"path":2303,"stem":2304},"Data APIs: Loaders та Actions","\u002Fjavascript\u002Freact\u002Freact-router\u002Fdata-loading","03.javascript\u002F04.react\u002F05.react-router\u002F05.data-loading",{"title":2306,"path":2307,"stem":2308},"Просунуті Патерни","\u002Fjavascript\u002Freact\u002Freact-router\u002Fadvanced-patterns","03.javascript\u002F04.react\u002F05.react-router\u002F06.advanced-patterns",{"title":2310,"path":2311,"stem":2312},"Legacy Routing: Компонентний підхід","\u002Fjavascript\u002Freact\u002Freact-router\u002Flegacy-routing","03.javascript\u002F04.react\u002F05.react-router\u002F07.legacy-routing",{"title":2314,"icon":132,"path":2315,"stem":2316,"children":2317},"Redux","\u002Fjavascript\u002Freact\u002Fredux","03.javascript\u002F04.react\u002F06.redux\u002Findex",[2318,2320,2336,2365,2374,2395,2411,2440],{"title":2319,"path":2315,"stem":2316},"Redux: Еволюція управління станом",{"title":14,"icon":15,"path":2321,"stem":2322,"children":2323,"page":59},"\u002Fjavascript\u002Freact\u002Fredux\u002Ffundamentals","03.javascript\u002F04.react\u002F06.redux\u002F01.fundamentals",[2324,2328,2332],{"title":2325,"path":2326,"stem":2327},"Вступ до State Management","\u002Fjavascript\u002Freact\u002Fredux\u002Ffundamentals\u002Fintro-state-management","03.javascript\u002F04.react\u002F06.redux\u002F01.fundamentals\u002F01.intro-state-management",{"title":2329,"path":2330,"stem":2331},"Філософія Redux та Три Принципи","\u002Fjavascript\u002Freact\u002Fredux\u002Ffundamentals\u002Fredux-philosophy","03.javascript\u002F04.react\u002F06.redux\u002F01.fundamentals\u002F02.redux-philosophy",{"title":2333,"path":2334,"stem":2335},"Чисті функції та Іммутабельність","\u002Fjavascript\u002Freact\u002Fredux\u002Ffundamentals\u002Fpure-functions-immutability","03.javascript\u002F04.react\u002F06.redux\u002F01.fundamentals\u002F03.pure-functions-immutability",{"title":2337,"icon":132,"path":2338,"stem":2339,"children":2340,"page":59},"Classic Redux","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux",[2341,2345,2349,2353,2357,2361],{"title":2342,"path":2343,"stem":2344},"Створення Store (Classic Redux)","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Fstore-setup","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F01.store-setup",{"title":2346,"path":2347,"stem":2348},"Actions, Constants та Action Creators","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Factions-constants","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F02.actions-constants",{"title":2350,"path":2351,"stem":2352},"Логіка Reducers","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Freducers","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F03.reducers",{"title":2354,"path":2355,"stem":2356},"Комбінування Reducers (Root Reducer)","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Fdata-flow","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F04.data-flow",{"title":2358,"path":2359,"stem":2360},"Підключення до React (React-Redux)","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Freact-redux-connection","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F05.react-redux-connection",{"title":2362,"path":2363,"stem":2364},"Middleware та Асинхронність (Redux Thunk)","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Fmiddleware-thunk","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F06.middleware-thunk",{"title":2366,"icon":132,"path":2367,"stem":2368,"children":2369,"page":59},"Transition To Rtk","\u002Fjavascript\u002Freact\u002Fredux\u002Ftransition-to-rtk","03.javascript\u002F04.react\u002F06.redux\u002F03.transition-to-rtk",[2370],{"title":2371,"path":2372,"stem":2373},"Проблеми класичного Redux","\u002Fjavascript\u002Freact\u002Fredux\u002Ftransition-to-rtk\u002Fproblems-with-classic","03.javascript\u002F04.react\u002F06.redux\u002F03.transition-to-rtk\u002F01.problems-with-classic",{"title":2375,"icon":132,"path":2376,"stem":2377,"children":2378,"page":59},"Redux Toolkit","\u002Fjavascript\u002Freact\u002Fredux\u002Fredux-toolkit","03.javascript\u002F04.react\u002F06.redux\u002F04.redux-toolkit",[2379,2383,2387,2391],{"title":2380,"path":2381,"stem":2382},"Налаштування Store з configureStore","\u002Fjavascript\u002Freact\u002Fredux\u002Fredux-toolkit\u002Fconfigure-store","03.javascript\u002F04.react\u002F06.redux\u002F04.redux-toolkit\u002F01.configure-store",{"title":2384,"path":2385,"stem":2386},"createSlice: Революція в Redux","\u002Fjavascript\u002Freact\u002Fredux\u002Fredux-toolkit\u002Fcreate-slice","03.javascript\u002F04.react\u002F06.redux\u002F04.redux-toolkit\u002F02.create-slice",{"title":2388,"path":2389,"stem":2390},"Асинхронність з createAsyncThunk","\u002Fjavascript\u002Freact\u002Fredux\u002Fredux-toolkit\u002Fasync-thunks","03.javascript\u002F04.react\u002F06.redux\u002F04.redux-toolkit\u002F03.async-thunks",{"title":2392,"path":2393,"stem":2394},"04. Entity Adapter: Керування нормалізованим станом","\u002Fjavascript\u002Freact\u002Fredux\u002Fredux-toolkit\u002Fentity-adapter","03.javascript\u002F04.react\u002F06.redux\u002F04.redux-toolkit\u002F04.entity-adapter",{"title":2396,"icon":92,"path":2397,"stem":2398,"children":2399,"page":59},"Advanced","\u002Fjavascript\u002Freact\u002Fredux\u002Fadvanced","03.javascript\u002F04.react\u002F06.redux\u002F05.advanced",[2400,2404,2408],{"title":2401,"path":2402,"stem":2403},"Мемоізація та Селектори: Повний Гайд по Reselect","\u002Fjavascript\u002Freact\u002Fredux\u002Fadvanced\u002Fselectors-reselect","03.javascript\u002F04.react\u002F06.redux\u002F05.advanced\u002F01.selectors-reselect",{"title":2405,"path":2406,"stem":2407},"RTK Query: Архітектура Серверного Кешу","\u002Fjavascript\u002Freact\u002Fredux\u002Fadvanced\u002Frtk-query-intro","03.javascript\u002F04.react\u002F06.redux\u002F05.advanced\u002F02.rtk-query-intro",{"title":2255,"path":2409,"stem":2410},"\u002Fjavascript\u002Freact\u002Fredux\u002Fadvanced\u002Farchitecture-best-practices","03.javascript\u002F04.react\u002F06.redux\u002F05.advanced\u002F03.architecture-best-practices",{"title":2412,"icon":132,"path":2413,"stem":2414,"children":2415,"page":59},"Project Kanban","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban",[2416,2420,2424,2428,2432,2436],{"title":2417,"path":2418,"stem":2419},"Проєкт: Kanban Board (Trello Clone)","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Fproject-overview","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F01.project-overview",{"title":2421,"path":2422,"stem":2423},"Налаштування та Типізація","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Fsetup-and-types","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F02.setup-and-types",{"title":2425,"path":2426,"stem":2427},"Board Slice: Серце Дошки","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Fboard-slice","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F03.board-slice",{"title":2429,"path":2430,"stem":2431},"Логіка Drag & Drop","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Fdrag-and-drop-logic","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F04.drag-and-drop-logic",{"title":2433,"path":2434,"stem":2435},"Інтеграція з RTK Query","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Frtk-query-integration","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F05.rtk-query-integration",{"title":2437,"path":2438,"stem":2439},"Optimistic Updates","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Foptimistic-updates","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F06.optimistic-updates",{"title":2441,"icon":132,"path":2442,"stem":2443,"children":2444,"page":59},"Testing","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting","03.javascript\u002F04.react\u002F06.redux\u002F07.testing",[2445,2449,2453,2457,2461],{"title":2446,"path":2447,"stem":2448},"Тестування Redux","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting\u002Fintro-testing","03.javascript\u002F04.react\u002F06.redux\u002F07.testing\u002F01.intro-testing",{"title":2450,"path":2451,"stem":2452},"Тестування Reducers","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting\u002Ftesting-reducers","03.javascript\u002F04.react\u002F06.redux\u002F07.testing\u002F02.testing-reducers",{"title":2454,"path":2455,"stem":2456},"Тестування Селекторів","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting\u002Ftesting-selectors","03.javascript\u002F04.react\u002F06.redux\u002F07.testing\u002F03.testing-selectors",{"title":2458,"path":2459,"stem":2460},"Тестування Компонентів (Integration)","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting\u002Ftesting-components","03.javascript\u002F04.react\u002F06.redux\u002F07.testing\u002F04.testing-components",{"title":2462,"path":2463,"stem":2464},"Тестування Async Thunks","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting\u002Ftesting-thunks","03.javascript\u002F04.react\u002F06.redux\u002F07.testing\u002F05.testing-thunks",{"title":2466,"icon":132,"path":2467,"stem":2468,"children":2469},"Ui Libraries","\u002Fjavascript\u002Freact\u002Fui-libraries","03.javascript\u002F04.react\u002F07.ui-libraries\u002Findex",[2470,2472,2476,2480,2484,2488,2492],{"title":2471,"path":2467,"stem":2468},"UI Бібліотеки в React",{"title":2473,"path":2474,"stem":2475},"Вступ до UI Бібліотек: Навіщо Винаходити Велосипед Двічі?","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fintroduction-to-ui-libraries","03.javascript\u002F04.react\u002F07.ui-libraries\u002F01.introduction-to-ui-libraries",{"title":2477,"path":2478,"stem":2479},"Філософія shadcn\u002Fui: \"Not a Component Library\"","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fshadcn-philosophy","03.javascript\u002F04.react\u002F07.ui-libraries\u002F02.shadcn-philosophy",{"title":2481,"path":2482,"stem":2483},"Установка та Налаштування shadcn\u002Fui","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fshadcn-installation","03.javascript\u002F04.react\u002F07.ui-libraries\u002F03.shadcn-installation",{"title":2485,"path":2486,"stem":2487},"Базові Компоненти shadcn\u002Fui: Фундамент Інтерфейсу","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fshadcn-components-basics","03.javascript\u002F04.react\u002F07.ui-libraries\u002F04.shadcn-components-basics",{"title":2489,"path":2490,"stem":2491},"Компоненти Форм: Побудова Інтерактивних Form","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fshadcn-components-forms","03.javascript\u002F04.react\u002F07.ui-libraries\u002F05.shadcn-components-forms",{"title":2493,"path":2494,"stem":2495},"Складні Компоненти: Dialog, Dropdown, Table та Command","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fshadcn-components-advanced","03.javascript\u002F04.react\u002F07.ui-libraries\u002F06.shadcn-components-advanced",{"title":2497,"icon":2498,"path":2499,"stem":2500,"children":2501,"page":59},"TypeScript","i-devicon-typescript","\u002Fjavascript\u002Ftypescript","03.javascript\u002F05.typescript",[2502,2506,2510,2514,2518,2522,2526,2530],{"title":2503,"path":2504,"stem":2505},"TypeScript: Броня для вашого коду","\u002Fjavascript\u002Ftypescript\u002Fintro-and-basic-types","03.javascript\u002F05.typescript\u002F01.intro-and-basic-types",{"title":2507,"path":2508,"stem":2509},"Майстерність Моделювання Даних: Інтерфейси та Просунуті Типи","\u002Fjavascript\u002Ftypescript\u002Finterfaces-and-advanced-types","03.javascript\u002F05.typescript\u002F02.interfaces-and-advanced-types",{"title":2511,"path":2512,"stem":2513},"Алхімія Типів: Generics та Utility Types","\u002Fjavascript\u002Ftypescript\u002Fgenerics-and-utilities","03.javascript\u002F05.typescript\u002F03.generics-and-utilities",{"title":2515,"path":2516,"stem":2517},"Архітектура та Шаблони: Класи в TypeScript","\u002Fjavascript\u002Ftypescript\u002Fclasses-and-oop","03.javascript\u002F05.typescript\u002F04.classes-and-oop",{"title":2519,"path":2520,"stem":2521},"Продакшн та Екосистема: Advanced Config & Workflow","\u002Fjavascript\u002Ftypescript\u002Fadvanced-patterns-and-config","03.javascript\u002F05.typescript\u002F05.advanced-patterns-and-config",{"title":2523,"path":2524,"stem":2525},"TypeScript у світі React","\u002Fjavascript\u002Ftypescript\u002Freact-basics","03.javascript\u002F05.typescript\u002F06.react-basics",{"title":2527,"path":2528,"stem":2529},"React + TypeScript: Продвинуті патерни","\u002Fjavascript\u002Ftypescript\u002Freact-advanced","03.javascript\u002F05.typescript\u002F07.react-advanced",{"title":2531,"path":2532,"stem":2533},"React + TypeScript: Екосистема та бібліотеки","\u002Fjavascript\u002Ftypescript\u002Freact-ecosystem","03.javascript\u002F05.typescript\u002F08.react-ecosystem",{"title":2535,"icon":2536,"path":2537,"stem":2538,"children":2539,"page":59},"Асинхронність","i-lucide-refresh-cw","\u002Fjavascript\u002Fasync-programming","03.javascript\u002F06.async-programming",[2540,2544,2548],{"title":2541,"path":2542,"stem":2543},"Event Loop: серце асинхронності в JavaScript","\u002Fjavascript\u002Fasync-programming\u002Fevent-loop-fundamentals","03.javascript\u002F06.async-programming\u002F01.event-loop-fundamentals",{"title":2545,"path":2546,"stem":2547},"Task Queue та Microtask Queue: пріоритети виконання","\u002Fjavascript\u002Fasync-programming\u002Ftask-queues","03.javascript\u002F06.async-programming\u002F02.task-queues",{"title":2549,"path":2550,"stem":2551},"Асинхронні патерни: від Callbacks до Async\u002FAwait","\u002Fjavascript\u002Fasync-programming\u002Fasync-patterns","03.javascript\u002F06.async-programming\u002F03.async-patterns",{"title":2553,"path":2554,"stem":2555},"Atomic Design","\u002Fjavascript\u002Fatomic-design","03.javascript\u002F2.atomic-design",{"title":2557,"icon":2558,"path":2559,"stem":2560,"children":2561,"page":59},"Java","i-devicon-java","\u002Fjava","04.java",[2562,2565,2568,2572,2576,2580,2584],{"title":162,"path":2563,"stem":2564},"\u002Fjava\u002Fdata-mapper-part1","04.java\u002F01.data-mapper-part1",{"title":166,"path":2566,"stem":2567},"\u002Fjava\u002Fdata-mapper-part2","04.java\u002F02.data-mapper-part2",{"title":2569,"path":2570,"stem":2571},"Service Layer: Організація бізнес-логіки","\u002Fjava\u002Fservice-layer","04.java\u002F03.service-layer",{"title":2573,"path":2574,"stem":2575},"Rich Domain Model та State Pattern","\u002Fjava\u002Frich-domain-model","04.java\u002F04.rich-domain-model",{"title":2577,"path":2578,"stem":2579},"Патерни для складної бізнес-логіки","\u002Fjava\u002Fbusiness-logic-patterns","04.java\u002F05.business-logic-patterns",{"title":2581,"path":2582,"stem":2583},"Обробка помилок та валідація","\u002Fjava\u002Ferror-handling-validation","04.java\u002F06.error-handling-validation",{"title":2585,"path":2586,"stem":2587,"children":2588,"page":59},"Проектування баз даних","\u002Fjava\u002Fpr2","04.java\u002Fpr2",[2589,2593,2597,2601,2605,2609,2613,2617,2621,2625,2629,2633,2637,2641,2645,2649,2653,2657,2661,2665,2669,2673,2677,2681,2685,2689,2693,2697,2701,2705,2709,2713,2717,2721,2725,2729,2733],{"title":2590,"path":2591,"stem":2592},"Концептуальне моделювання: Мистецтво розуміння предметної області","\u002Fjava\u002Fpr2\u002Fconceptual-modeling","04.java\u002Fpr2\u002F01.conceptual-modeling",{"title":2594,"path":2595,"stem":2596},"Логічне моделювання: Від бізнес-ідей до структур даних","\u002Fjava\u002Fpr2\u002Flogical-modeling","04.java\u002Fpr2\u002F02.logical-modeling",{"title":2598,"path":2599,"stem":2600},"Нормалізація: Гігієна даних та боротьба з аномаліями","\u002Fjava\u002Fpr2\u002Fnormalization","04.java\u002Fpr2\u002F03.normalization",{"title":2602,"path":2603,"stem":2604},"Фізична схема: Від абстракції до DDL","\u002Fjava\u002Fpr2\u002Fphysical-schema","04.java\u002Fpr2\u002F04.physical-schema",{"title":2606,"path":2607,"stem":2608},"Архітектурна класифікація таблиць","\u002Fjava\u002Fpr2\u002Ftable-classification","04.java\u002Fpr2\u002F05.table-classification",{"title":2610,"path":2611,"stem":2612},"Database Migrations: Версіонування схеми з Flyway","\u002Fjava\u002Fpr2\u002Fdatabase-migrations","04.java\u002Fpr2\u002F06.database-migrations",{"title":2614,"path":2615,"stem":2616},"А що, якби це була не реляційна БД?","\u002Fjava\u002Fpr2\u002Fbeyond-relational","04.java\u002Fpr2\u002F07.beyond-relational",{"title":2618,"path":2619,"stem":2620},"Object-Relational Impedance Mismatch: Два світи, що не хочуть дружити","\u002Fjava\u002Fpr2\u002Fimpedance-mismatch","04.java\u002Fpr2\u002F09.impedance-mismatch",{"title":2622,"path":2623,"stem":2624},"JDBC: Перший контакт із базою даних","\u002Fjava\u002Fpr2\u002Fjdbc-fundamentals","04.java\u002Fpr2\u002F10.jdbc-fundamentals",{"title":2626,"path":2627,"stem":2628},"Якість коду: Spotless, SpotBugs та SonarQube","\u002Fjava\u002Fpr2\u002F10a.code-quality","04.java\u002Fpr2\u002F10a.code-quality",{"title":2630,"path":2631,"stem":2632},"Connection Pool: Патерн Object Pool для JDBC-з'єднань","\u002Fjava\u002Fpr2\u002Fconnection-pool","04.java\u002Fpr2\u002F11.connection-pool",{"title":2634,"path":2635,"stem":2636},"Row Data Gateway: Об'єкт як обгортка рядка таблиці","\u002Fjava\u002Fpr2\u002Frow-data-gateway","04.java\u002Fpr2\u002F12.row-data-gateway",{"title":2638,"path":2639,"stem":2640},"Table Data Gateway: Фасад таблиці як архітектурний відступ","\u002Fjava\u002Fpr2\u002Ftable-data-gateway","04.java\u002Fpr2\u002F13.table-data-gateway",{"title":2642,"path":2643,"stem":2644},"Repository + Data Mapper: Правильна шарова архітектура з JDBC","\u002Fjava\u002Fpr2\u002Frepository-data-mapper","04.java\u002Fpr2\u002F14.repository-data-mapper",{"title":2646,"path":2647,"stem":2648},"Identity Map: Кешування сутностей у рамках сесії","\u002Fjava\u002Fpr2\u002Fidentity-map","04.java\u002Fpr2\u002F15.identity-map",{"title":2650,"path":2651,"stem":2652},"Unit of Work: Відстеження змін і координація JDBC-транзакцій","\u002Fjava\u002Fpr2\u002Funit-of-work","04.java\u002Fpr2\u002F16.unit-of-work",{"title":2654,"path":2655,"stem":2656},"Strategy: Замінювані SQL-стратегії для підтримки різних СУБД","\u002Fjava\u002Fpr2\u002Fstrategy-sql","04.java\u002Fpr2\u002F17.strategy-sql",{"title":2658,"path":2659,"stem":2660},"Proxy: Lazy Loading для One-To-Many колекцій","\u002Fjava\u002Fpr2\u002Fproxy-lazy-loading","04.java\u002Fpr2\u002F18.proxy-lazy-loading",{"title":2662,"path":2663,"stem":2664},"Generic Repository через Java Reflection: анотації та динамічний SQL","\u002Fjava\u002Fpr2\u002Fgeneric-repository-reflection","04.java\u002Fpr2\u002F19.generic-repository-reflection",{"title":2666,"path":2667,"stem":2668},"Specification Pattern: Композиція бізнес-правил для складних запитів","\u002Fjava\u002Fpr2\u002Fspecification-pattern","04.java\u002Fpr2\u002F20.specification-pattern",{"title":2670,"path":2671,"stem":2672},"Розширені можливості Specification Pattern: підзапити, агрегації та гібридний підхід","\u002Fjava\u002Fpr2\u002F20a.advanced-specifications","04.java\u002Fpr2\u002F20a.advanced-specifications",{"title":2674,"path":2675,"stem":2676},"Асинхронність у JDBC: Від блокуючих викликів до CompletableFuture","\u002Fjava\u002Fpr2\u002Fasynchronous-jdbc","04.java\u002Fpr2\u002F21.asynchronous-jdbc",{"title":2678,"path":2679,"stem":2680},"Інтеграційне тестування JDBC-репозиторіїв: Embedded H2 та патерн AAA","\u002Fjava\u002Fpr2\u002Fintegration-testing-h2","04.java\u002Fpr2\u002F22.integration-testing-h2",{"title":2682,"path":2683,"stem":2684},"Testcontainers: Тестування з реальною PostgreSQL у Docker-контейнерах","\u002Fjava\u002Fpr2\u002Fintegration-testing-testcontainers","04.java\u002Fpr2\u002F23.integration-testing-testcontainers",{"title":2686,"path":2687,"stem":2688},"Google Guice: Впровадження залежностей у JavaFX-проєкті","\u002Fjava\u002Fpr2\u002Fdependency-injection-guice","04.java\u002Fpr2\u002F24.dependency-injection-guice",{"title":2690,"path":2691,"stem":2692},"JavaFX: Основи побудови графічних інтерфейсів","\u002Fjava\u002Fpr2\u002Fjavafx-fundamentals","04.java\u002Fpr2\u002F25.javafx-fundamentals",{"title":2694,"path":2695,"stem":2696},"Properties та Bindings: Реактивність у JavaFX","\u002Fjava\u002Fpr2\u002Fjavafx-properties-bindings","04.java\u002Fpr2\u002F26.javafx-properties-bindings",{"title":2698,"path":2699,"stem":2700},"MVC vs MVP vs MVVM: Еволюція архітектурних патернів UI","\u002Fjava\u002Fpr2\u002Fui-architecture-patterns","04.java\u002Fpr2\u002F27.ui-architecture-patterns",{"title":2702,"path":2703,"stem":2704},"MVVM на практиці: Побудова ViewModel","\u002Fjava\u002Fpr2\u002Fmvvm-viewmodel-implementation","04.java\u002Fpr2\u002F28.mvvm-viewmodel-implementation",{"title":2706,"path":2707,"stem":2708},"View та Controller: Зв'язування з ViewModel через FXML","\u002Fjava\u002Fpr2\u002Fmvvm-view-controller","04.java\u002Fpr2\u002F29.mvvm-view-controller",{"title":2710,"path":2711,"stem":2712},"Інтеграція MVVM з Guice: Автоматична ін'єкція залежностей","\u002Fjava\u002Fpr2\u002Fmvvm-guice-integration","04.java\u002Fpr2\u002F30.mvvm-guice-integration",{"title":2714,"path":2715,"stem":2716},"Валідація та обробка помилок у MVVM","\u002Fjava\u002Fpr2\u002Fmvvm-validation-error-handling","04.java\u002Fpr2\u002F31.mvvm-validation-error-handling",{"title":2718,"path":2719,"stem":2720},"Навігація та управління екранами у JavaFX MVVM","\u002Fjava\u002Fpr2\u002Fmvvm-navigation-screen-management","04.java\u002Fpr2\u002F32.mvvm-navigation-screen-management",{"title":2722,"path":2723,"stem":2724},"Тестування JavaFX MVVM-додатків","\u002Fjava\u002Fpr2\u002Fmvvm-testing","04.java\u002Fpr2\u002F33.mvvm-testing",{"title":2726,"path":2727,"stem":2728},"Стилізація та теми у JavaFX: CSS та User Experience","\u002Fjava\u002Fpr2\u002Fjavafx-styling-themes","04.java\u002Fpr2\u002F34.javafx-styling-themes",{"title":2730,"path":2731,"stem":2732},"AtlantaFX: Сучасні теми для JavaFX додатків","\u002Fjava\u002Fpr2\u002Fatlantafx-modern-themes","04.java\u002Fpr2\u002F35.atlantafx-modern-themes",{"title":2734,"path":2735,"stem":2736},"Пакування та розповсюдження JavaFX-додатків","\u002Fjava\u002Fpr2\u002Fjar-packaging-distribution","04.java\u002Fpr2\u002F36.jar-packaging-distribution",{"title":2738,"icon":2739,"path":2740,"stem":2741,"children":2742,"page":59},"Python","i-devicon-python","\u002Fpython","05.python",[2743,2747,2750,2754,2758,2762,2766,2770,2774,2778,2782,2786,2790,2794,2798,2859],{"title":2744,"path":2745,"stem":2746},"Модулі, Пакети та Віртуальні Середовища","\u002Fpython\u002Fmodules-packages-venv","05.python\u002F00.modules-packages-venv",{"title":71,"path":2748,"stem":2749},"\u002Fpython\u002Fclasses-objects","05.python\u002F01.classes-objects",{"title":2751,"path":2752,"stem":2753},"Інкапсуляція, Керування Доступом та Властивості","\u002Fpython\u002Fencapsulation","05.python\u002F02.encapsulation",{"title":2755,"path":2756,"stem":2757},"Наслідування, MRO та суперсила super()","\u002Fpython\u002Finheritance-mro","05.python\u002F03.inheritance-mro",{"title":2759,"path":2760,"stem":2761},"Абстракція — ABC проти Статичних Протоколів (PEP 544)","\u002Fpython\u002Fabstraction-protocols","05.python\u002F04.abstraction-protocols",{"title":2763,"path":2764,"stem":2765},"Магічні методи (Dunder) та Емуляція протоколів","\u002Fpython\u002Fdunder-methods","05.python\u002F05.dunder-methods",{"title":2767,"path":2768,"stem":2769},"Декоратори та Керування життєвим циклом методів","\u002Fpython\u002Fdecorators-static-class","05.python\u002F06.decorators-static-class",{"title":2771,"path":2772,"stem":2773},"Дескриптори — Магія доступу до атрибутів","\u002Fpython\u002Fdescriptors","05.python\u002F07.descriptors",{"title":2775,"path":2776,"stem":2777},"Метакласи — Динамічне створення класів під капотом CPython","\u002Fpython\u002Fmetaclasses","05.python\u002F08.metaclasses",{"title":2779,"path":2780,"stem":2781},"Dataclasses, NamedTuple та сучасні контейнери Python","\u002Fpython\u002Fmodern-containers","05.python\u002F09.modern-containers",{"title":2783,"path":2784,"stem":2785},"GIL та модель конкурентності CPython — фундамент перед потоками і процесами","\u002Fpython\u002Fgil-concurrency-intro","05.python\u002F11.gil-concurrency-intro",{"title":2787,"path":2788,"stem":2789},"Threading — конкурентність для I\u002FO-bound задач","\u002Fpython\u002Fthreading","05.python\u002F12.threading",{"title":2791,"path":2792,"stem":2793},"Multiprocessing — справжній паралелізм для CPU-bound задач","\u002Fpython\u002Fmultiprocessing","05.python\u002F13.multiprocessing",{"title":2795,"path":2796,"stem":2797},"asyncio — кооперативна конкурентність та event loop","\u002Fpython\u002Fasyncio","05.python\u002F14.asyncio",{"title":2799,"icon":92,"path":2800,"stem":2801,"children":2802,"page":59},"FastAPI","\u002Fpython\u002Ffastapi","05.python\u002Ffastapi",[2803,2807,2811,2815,2819,2823,2827,2831,2835,2839,2843,2847,2851,2855],{"title":2804,"path":2805,"stem":2806},"Глибокий Typing та Pydantic v2 — від анотацій до валідації","\u002Fpython\u002Ffastapi\u002Ftyping-pydantic","05.python\u002Ffastapi\u002F15.typing-pydantic",{"title":2808,"path":2809,"stem":2810},"WSGI, ASGI та Python Web-екосистема","\u002Fpython\u002Ffastapi\u002Fwsgi-asgi-ecosystem","05.python\u002Ffastapi\u002F16.wsgi-asgi-ecosystem",{"title":2812,"path":2813,"stem":2814},"FastAPI: Перший додаток, Uvicorn та OpenAPI","\u002Fpython\u002Ffastapi\u002Ffastapi-intro","05.python\u002Ffastapi\u002F17.fastapi-intro",{"title":2816,"path":2817,"stem":2818},"Маршрутизація, параметри запитів та APIRouter","\u002Fpython\u002Ffastapi\u002Ffastapi-routing-params","05.python\u002Ffastapi\u002F18.fastapi-routing-params",{"title":2820,"path":2821,"stem":2822},"Pydantic v2 у FastAPI — схеми, валідація та серіалізація","\u002Fpython\u002Ffastapi\u002Ffastapi-pydantic-schemas","05.python\u002Ffastapi\u002F19.fastapi-pydantic-schemas",{"title":2824,"path":2825,"stem":2826},"Dependency Injection — серце архітектури FastAPI","\u002Fpython\u002Ffastapi\u002Ffastapi-dependency-injection","05.python\u002Ffastapi\u002F20.fastapi-dependency-injection",{"title":2828,"path":2829,"stem":2830},"Обробка помилок, Middleware та CORS у FastAPI","\u002Fpython\u002Ffastapi\u002Ffastapi-errors-middleware","05.python\u002Ffastapi\u002F21.fastapi-errors-middleware",{"title":2832,"path":2833,"stem":2834},"SQLAlchemy 2.0 — ORM, Core та Async Engine","\u002Fpython\u002Ffastapi\u002Fsqlalchemy-orm","05.python\u002Ffastapi\u002F22.sqlalchemy-orm",{"title":2836,"path":2837,"stem":2838},"Alembic — міграції бази даних","\u002Fpython\u002Ffastapi\u002Falembic-migrations","05.python\u002Ffastapi\u002F23.alembic-migrations",{"title":2840,"path":2841,"stem":2842},"Repository Pattern та Clean Architecture у FastAPI","\u002Fpython\u002Ffastapi\u002Ffastapi-repository-clean-arch","05.python\u002Ffastapi\u002F24.fastapi-repository-clean-arch",{"title":2844,"path":2845,"stem":2846},"Автентифікація та авторизація — JWT, OAuth2, RBAC","\u002Fpython\u002Ffastapi\u002Ffastapi-auth-security","05.python\u002Ffastapi\u002F25.fastapi-auth-security",{"title":2848,"path":2849,"stem":2850},"Тестування FastAPI — pytest, httpx, fixtures","\u002Fpython\u002Ffastapi\u002Ffastapi-testing","05.python\u002Ffastapi\u002F26.fastapi-testing",{"title":2852,"path":2853,"stem":2854},"Async на повну — Background Tasks, WebSockets, SSE та Celery","\u002Fpython\u002Ffastapi\u002Ffastapi-async-advanced","05.python\u002Ffastapi\u002F27.fastapi-async-advanced",{"title":2856,"path":2857,"stem":2858},"Deployment — Docker, CI\u002FCD, Monitoring","\u002Fpython\u002Ffastapi\u002Ffastapi-deployment","05.python\u002Ffastapi\u002F28.fastapi-deployment",{"title":2860,"path":2861,"stem":2862},"[object Object]","\u002Fpython\u002Foop-plan","05.python\u002Foop-plan",{"title":2864,"icon":2865,"path":2866,"stem":2867,"children":2868,"page":59},"Бази даних","i-lucide-database","\u002Fdatabases","06.databases",[2869,2899,2922,2959,2988,3006,3040,3052,3061],{"title":2870,"icon":2871,"path":2872,"stem":2873,"children":2874,"page":59},"Intro","i-lucide-play","\u002Fdatabases\u002Fintro","06.databases\u002F01.intro",[2875,2879,2883,2887,2891,2895],{"title":2876,"path":2877,"stem":2878},"Введення в теорію баз даних","\u002Fdatabases\u002Fintro\u002Fintroduction-to-databases","06.databases\u002F01.intro\u002F01.introduction-to-databases",{"title":2880,"path":2881,"stem":2882},"Реляційна модель даних","\u002Fdatabases\u002Fintro\u002Frelational-model-theory","06.databases\u002F01.intro\u002F02.relational-model-theory",{"title":2884,"path":2885,"stem":2886},"ER-моделювання","\u002Fdatabases\u002Fintro\u002Fer-modeling","06.databases\u002F01.intro\u002F03.er-modeling",{"title":2888,"path":2889,"stem":2890},"Логічне проектування БД","\u002Fdatabases\u002Fintro\u002Flogical-schema","06.databases\u002F01.intro\u002F04.logical-schema",{"title":2892,"path":2893,"stem":2894},"Класифікація таблиць","\u002Fdatabases\u002Fintro\u002Ftable-classification","06.databases\u002F01.intro\u002F05.table-classification",{"title":2896,"path":2897,"stem":2898},"PlantUML для баз даних","\u002Fdatabases\u002Fintro\u002Fplantuml-diagrams","06.databases\u002F01.intro\u002F06.plantuml-diagrams",{"title":2900,"icon":2865,"path":2901,"stem":2902,"children":2903,"page":59},"MS SQL Server Start","\u002Fdatabases\u002Fms-sql-server-start","06.databases\u002F02.ms-sql-server-start",[2904,2908,2914,2918],{"title":2905,"path":2906,"stem":2907},"Типи даних у MS SQL Server","\u002Fdatabases\u002Fms-sql-server-start\u002Fdata-types","06.databases\u002F02.ms-sql-server-start\u002F01.data-types",{"title":2909,"path":2910,"stem":2911,"children":2912},"Індекси у MS SQL Server","\u002Fdatabases\u002Fms-sql-server-start\u002Fsql-indexes","06.databases\u002F02.ms-sql-server-start\u002F02.sql-indexes",[2913],{"title":2909,"path":2910,"stem":2911},{"title":2915,"path":2916,"stem":2917},"Системні бази даних MS SQL Server","\u002Fdatabases\u002Fms-sql-server-start\u002Fsystem-databases","06.databases\u002F02.ms-sql-server-start\u002F03.system-databases",{"title":2919,"path":2920,"stem":2921},"Огляд мови SQL та запитів","\u002Fdatabases\u002Fms-sql-server-start\u002Fsql-queries-overview","06.databases\u002F02.ms-sql-server-start\u002F04.sql-queries-overview",{"title":2923,"icon":2865,"path":2924,"stem":2925,"children":2926,"page":59},"SQL","\u002Fdatabases\u002Fsql","06.databases\u002F03.sql",[2927,2931,2935,2939,2943,2947,2951,2955],{"title":2928,"path":2929,"stem":2930},"Налаштування демонстраційної бази даних","\u002Fdatabases\u002Fsql\u002Fsample-database-setup","06.databases\u002F03.sql\u002F00.sample-database-setup",{"title":2932,"path":2933,"stem":2934},"DDL - Створення таблиць (CREATE TABLE)","\u002Fdatabases\u002Fsql\u002Fddl-create-table","06.databases\u002F03.sql\u002F01.ddl-create-table",{"title":2936,"path":2937,"stem":2938},"DDL - Зміна та видалення таблиць (ALTER, DROP)","\u002Fdatabases\u002Fsql\u002Fddl-alter-drop-table","06.databases\u002F03.sql\u002F02.ddl-alter-drop-table",{"title":2940,"path":2941,"stem":2942},"SELECT запити - Основи","\u002Fdatabases\u002Fsql\u002Fselect-queries-fundamentals","06.databases\u002F03.sql\u002F03.select-queries-fundamentals",{"title":2944,"path":2945,"stem":2946},"SELECT запити - Розширені можливості","\u002Fdatabases\u002Fsql\u002Fselect-queries-advanced","06.databases\u002F03.sql\u002F04.select-queries-advanced",{"title":2948,"path":2949,"stem":2950},"INSERT запити - Додавання даних","\u002Fdatabases\u002Fsql\u002Finsert-queries","06.databases\u002F03.sql\u002F05.insert-queries",{"title":2952,"path":2953,"stem":2954},"UPDATE та DELETE запити","\u002Fdatabases\u002Fsql\u002Fupdate-delete-queries","06.databases\u002F03.sql\u002F06.update-delete-queries",{"title":2956,"path":2957,"stem":2958},"Транзакції в SQL","\u002Fdatabases\u002Fsql\u002Ftransactions","06.databases\u002F03.sql\u002F07.transactions",{"title":2960,"icon":2865,"path":2961,"stem":2962,"children":2963,"page":59},"Multi Table Databases","\u002Fdatabases\u002Fmulti-table-databases","06.databases\u002F04.multi-table-databases",[2964,2968,2972,2976,2980,2984],{"title":2965,"path":2966,"stem":2967},"Зв'язки та нормалізація БД","\u002Fdatabases\u002Fmulti-table-databases\u002Frelationships-and-normalization","06.databases\u002F04.multi-table-databases\u002F00.relationships-and-normalization",{"title":2969,"path":2970,"stem":2971},"INNER JOIN - З'єднання таблиць","\u002Fdatabases\u002Fmulti-table-databases\u002Finner-join","06.databases\u002F04.multi-table-databases\u002F01.inner-join",{"title":2973,"path":2974,"stem":2975},"OUTER JOINs - LEFT, RIGHT, FULL","\u002Fdatabases\u002Fmulti-table-databases\u002Fouter-joins","06.databases\u002F04.multi-table-databases\u002F02.outer-joins",{"title":2977,"path":2978,"stem":2979},"CROSS та SELF JOINs","\u002Fdatabases\u002Fmulti-table-databases\u002Fcross-self-joins","06.databases\u002F04.multi-table-databases\u002F03.cross-self-joins",{"title":2981,"path":2982,"stem":2983},"Підзапити (Subqueries)","\u002Fdatabases\u002Fmulti-table-databases\u002Fsubqueries","06.databases\u002F04.multi-table-databases\u002F04.subqueries",{"title":2985,"path":2986,"stem":2987},"Агрегації з JOIN","\u002Fdatabases\u002Fmulti-table-databases\u002Faggregations-with-joins","06.databases\u002F04.multi-table-databases\u002F05.aggregations-with-joins",{"title":2989,"icon":2990,"path":2991,"stem":2992,"children":2993,"page":59},"Aggregate Functions","i-lucide-calculator","\u002Fdatabases\u002Faggregate-functions","06.databases\u002F05.aggregate-functions",[2994,2998,3002],{"title":2995,"path":2996,"stem":2997},"Функції агрегування в MS SQL Server","\u002Fdatabases\u002Faggregate-functions\u002Fintroduction-aggregate-functions","06.databases\u002F05.aggregate-functions\u002F01.introduction-aggregate-functions",{"title":2999,"path":3000,"stem":3001},"Групування даних в MS SQL Server","\u002Fdatabases\u002Faggregate-functions\u002Fgrouping-data","06.databases\u002F05.aggregate-functions\u002F02.grouping-data",{"title":3003,"path":3004,"stem":3005},"Підзапити з агрегатними функціями","\u002Fdatabases\u002Faggregate-functions\u002Fsubqueries-aggregates","06.databases\u002F05.aggregate-functions\u002F03.subqueries-aggregates",{"title":3007,"icon":3008,"path":3009,"stem":3010,"children":3011,"page":59},"Тригери та зберігаємі процедури","i-lucide-database-zap","\u002Fdatabases\u002Ftriggers-stored-procedures","06.databases\u002F07.triggers-stored-procedures",[3012,3016,3020,3024,3028,3032,3036],{"title":3013,"path":3014,"stem":3015},"DML-тригери","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Fdml-triggers","06.databases\u002F07.triggers-stored-procedures\u002F01.dml-triggers",{"title":3017,"path":3018,"stem":3019},"DDL-тригери","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Fddl-triggers","06.databases\u002F07.triggers-stored-procedures\u002F02.ddl-triggers",{"title":3021,"path":3022,"stem":3023},"Transact-SQL розширення","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Ftransact-sql-extensions","06.databases\u002F07.triggers-stored-procedures\u002F03.transact-sql-extensions",{"title":3025,"path":3026,"stem":3027},"Транзакції","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Ftransactions","06.databases\u002F07.triggers-stored-procedures\u002F04.transactions",{"title":3029,"path":3030,"stem":3031},"Зберігаємі процедури","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Fstored-procedures","06.databases\u002F07.triggers-stored-procedures\u002F05.stored-procedures",{"title":3033,"path":3034,"stem":3035},"Користувацькі функції","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Fuser-defined-functions","06.databases\u002F07.triggers-stored-procedures\u002F06.user-defined-functions",{"title":3037,"path":3038,"stem":3039},"Безпека баз даних","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Fsecurity","06.databases\u002F07.triggers-stored-procedures\u002F08.security",{"title":3037,"icon":793,"path":3041,"stem":3042,"children":3043,"page":59},"\u002Fdatabases\u002Fsecurity","06.databases\u002F08.security",[3044,3048],{"title":3045,"path":3046,"stem":3047},"Вступ до безпеки баз даних","\u002Fdatabases\u002Fsecurity\u002Fintroduction","06.databases\u002F08.security\u002F01.introduction",{"title":3049,"path":3050,"stem":3051},"Системні представлення та метадані","\u002Fdatabases\u002Fsecurity\u002Fsystem-views","06.databases\u002F08.security\u002F02.system-views",{"title":3053,"icon":3054,"path":3055,"stem":3056,"children":3057,"page":59},"Резервне копіювання та відновлення","i-lucide-database-backup","\u002Fdatabases\u002Fbackup-recovery","06.databases\u002F09.backup-recovery",[3058],{"title":3053,"path":3059,"stem":3060},"\u002Fdatabases\u002Fbackup-recovery\u002Fbackup-restore","06.databases\u002F09.backup-recovery\u002F01.backup-restore",{"title":3062,"icon":3063,"path":3064,"stem":3065,"children":3066,"page":59},"Повнотекстовий пошук","i-lucide-search","\u002Fdatabases\u002Ffull-text-search","06.databases\u002F10.full-text-search",[3067],{"title":3062,"path":3068,"stem":3069},"\u002Fdatabases\u002Ffull-text-search\u002Ffull-text-search","06.databases\u002F10.full-text-search\u002F01.full-text-search",{"title":3071,"icon":3072,"path":3073,"stem":3074,"children":3075,"page":59},"Tools","i-lucide-wrench","\u002Ftools","07.tools",[3076,3152],{"title":3077,"icon":3078,"path":3079,"stem":3080,"children":3081},"Docker","i-simple-icons-docker","\u002Ftools\u002Fdocker","07.tools\u002F01.docker\u002Findex",[3082,3084,3088,3092,3096,3100,3104,3108,3112,3116,3120,3124,3128,3132,3136,3140,3144,3148],{"title":3083,"path":3079,"stem":3080},"Docker: від нуля до production",{"title":3085,"path":3086,"stem":3087},"Контейнеризація — від проблеми до рішення","\u002Ftools\u002Fdocker\u002Fcontainerization-concept","07.tools\u002F01.docker\u002F01.containerization-concept",{"title":3089,"path":3090,"stem":3091},"Docker — що це і навіщо?","\u002Ftools\u002Fdocker\u002Fdocker-what-and-why","07.tools\u002F01.docker\u002F02.docker-what-and-why",{"title":3093,"path":3094,"stem":3095},"Архітектура Docker Engine","\u002Ftools\u002Fdocker\u002Fdocker-architecture","07.tools\u002F01.docker\u002F03.docker-architecture",{"title":3097,"path":3098,"stem":3099},"Встановлення Docker","\u002Ftools\u002Fdocker\u002Finstallation","07.tools\u002F01.docker\u002F04.installation",{"title":3101,"path":3102,"stem":3103},"Перший контейнер — docker run","\u002Ftools\u002Fdocker\u002Ffirst-container","07.tools\u002F01.docker\u002F05.first-container",{"title":3105,"path":3106,"stem":3107},"Життєвий цикл контейнера","\u002Ftools\u002Fdocker\u002Fcontainer-lifecycle","07.tools\u002F01.docker\u002F06.container-lifecycle",{"title":3109,"path":3110,"stem":3111},"Docker Images — фундаментальні концепції","\u002Ftools\u002Fdocker\u002Fdocker-images-fundamentals","07.tools\u002F01.docker\u002F07.docker-images-fundamentals",{"title":3113,"path":3114,"stem":3115},"Dockerfile — основи","\u002Ftools\u002Fdocker\u002Fdockerfile-basics","07.tools\u002F01.docker\u002F08.dockerfile-basics",{"title":3117,"path":3118,"stem":3119},"Dockerfile — просунуті техніки","\u002Ftools\u002Fdocker\u002Fdockerfile-advanced","07.tools\u002F01.docker\u002F09.dockerfile-advanced",{"title":3121,"path":3122,"stem":3123},"Build Context та кешування шарів","\u002Ftools\u002Fdocker\u002Fbuild-context-and-cache","07.tools\u002F01.docker\u002F10.build-context-and-cache",{"title":3125,"path":3126,"stem":3127},"Реєстри Docker-образів","\u002Ftools\u002Fdocker\u002Fimage-registries","07.tools\u002F01.docker\u002F11.image-registries",{"title":3129,"path":3130,"stem":3131},"Контейнеризація .NET додатків","\u002Ftools\u002Fdocker\u002Fdotnet-containerization","07.tools\u002F01.docker\u002F12.dotnet-containerization",{"title":3133,"path":3134,"stem":3135},"Томи та збереження даних","\u002Ftools\u002Fdocker\u002Fvolumes-and-data","07.tools\u002F01.docker\u002F13.volumes-and-data",{"title":3137,"path":3138,"stem":3139},"Основи мережі в Docker","\u002Ftools\u002Fdocker\u002Fnetworking-basics","07.tools\u002F01.docker\u002F14.networking-basics",{"title":3141,"path":3142,"stem":3143},"Змінні оточення та конфігурація","\u002Ftools\u002Fdocker\u002Fenvironment-and-configuration","07.tools\u002F01.docker\u002F15.environment-and-configuration",{"title":3145,"path":3146,"stem":3147},"Docker Compose — оркестрація контейнерів","\u002Ftools\u002Fdocker\u002Fdocker-compose-basics","07.tools\u002F01.docker\u002F16.docker-compose-basics",{"title":3149,"path":3150,"stem":3151},"Docker Compose — Multi-Service застосунки","\u002Ftools\u002Fdocker\u002Fcompose-multi-service","07.tools\u002F01.docker\u002F17.compose-multi-service",{"title":3153,"icon":3154,"path":3155,"stem":3156,"children":3157},"Kubernetes","simple-icons:kubernetes","\u002Ftools\u002Fkubernetes","07.tools\u002F02.kubernetes\u002Findex",[3158,3160,3164,3168,3172,3176,3180,3184,3188],{"title":3159,"path":3155,"stem":3156},"Kubernetes: від розробки до production",{"title":3161,"path":3162,"stem":3163},"Kubernetes — коли Docker Compose більше не вистачає","\u002Ftools\u002Fkubernetes\u002Fwhy-kubernetes","07.tools\u002F02.kubernetes\u002F01.why-kubernetes",{"title":3165,"path":3166,"stem":3167},"Архітектура Kubernetes — анатомія кластера","\u002Ftools\u002Fkubernetes\u002Fkubernetes-architecture","07.tools\u002F02.kubernetes\u002F02.kubernetes-architecture",{"title":3169,"path":3170,"stem":3171},"Локальне середовище — minikube, kind та k3s","\u002Ftools\u002Fkubernetes\u002Flocal-environment","07.tools\u002F02.kubernetes\u002F03.local-environment",{"title":3173,"path":3174,"stem":3175},"Pod — атомарна одиниця Kubernetes","\u002Ftools\u002Fkubernetes\u002Fpods-and-containers","07.tools\u002F02.kubernetes\u002F04.pods-and-containers",{"title":3177,"path":3178,"stem":3179},"Патерни використання Pod","\u002Ftools\u002Fkubernetes\u002Fpod-patterns","07.tools\u002F02.kubernetes\u002F05.pod-patterns",{"title":3181,"path":3182,"stem":3183},"Deployment — декларативне управління Pod","\u002Ftools\u002Fkubernetes\u002Fdeployment-basics","07.tools\u002F02.kubernetes\u002F06.deployment-basics",{"title":3185,"path":3186,"stem":3187},"Rolling Updates та управління життєвим циклом Deployment","\u002Ftools\u002Fkubernetes\u002Fdeployment-rolling-updates","07.tools\u002F02.kubernetes\u002F07.deployment-rolling-updates",{"title":3189,"path":3190,"stem":3191},"Service — мережева абстракція для Pod","\u002Ftools\u002Fkubernetes\u002Fservices-networking","07.tools\u002F02.kubernetes\u002F08.services-networking",{"title":3193,"icon":3194,"path":3195,"stem":3196,"children":3197,"page":59},"Software Engineering","i-lucide-code-2","\u002Fsoftware-engineering","09.software-engineering",[3198,3202,3206,3210,3214,3218,3222,3226,3230,3234,3238],{"title":3199,"path":3200,"stem":3201},"1. Аналіз предметної області. Експертні знання та складність","\u002Fsoftware-engineering\u002Fintro-subdomains","09.software-engineering\u002F01.intro-subdomains",{"title":3203,"path":3204,"stem":3205},"2. Обмежені контексти. Інтеграція обмежених контекстів","\u002Fsoftware-engineering\u002Fintegrating-limited-contexts","09.software-engineering\u002F02.integrating-limited-contexts",{"title":3207,"path":3208,"stem":3209},"3. Реалізація простої бізнес-логіки","\u002Fsoftware-engineering\u002Fsimple","09.software-engineering\u002F03.simple",{"title":3211,"path":3212,"stem":3213},"4. Опрацювання складної бізнес-логіки","\u002Fsoftware-engineering\u002Fcomplex-business-logic","09.software-engineering\u002F04.complex-business-logic",{"title":3215,"path":3216,"stem":3217},"5. Моделювання фактора часу. Подієво-орієнтована архітектура.","\u002Fsoftware-engineering\u002Fmodelling-the-time-factor","09.software-engineering\u002F05.modelling-the-time-factor",{"title":3219,"path":3220,"stem":3221},"6. Архітектурні патерни","\u002Fsoftware-engineering\u002Farchitectural-patterns","09.software-engineering\u002F06.architectural-patterns",{"title":3223,"path":3224,"stem":3225},"Паттерни взаємодії","\u002Fsoftware-engineering\u002Fpatterns-of-interaction","09.software-engineering\u002F07.patterns-of-interaction",{"title":3227,"path":3228,"stem":3229},"Евристика проєктування","\u002Fsoftware-engineering\u002Fdesign-heuristics","09.software-engineering\u002F08.design-heuristics",{"title":3231,"path":3232,"stem":3233},"Еволюція проєктних рішень","\u002Fsoftware-engineering\u002Fevolution-of-design-solutions","09.software-engineering\u002F09.evolution-of-design-solutions",{"title":3235,"path":3236,"stem":3237},"EventStorming","\u002Fsoftware-engineering\u002Feventstorming","09.software-engineering\u002F10.eventstorming",{"title":3239,"path":3240,"stem":3241},"DDD на практиці","\u002Fsoftware-engineering\u002Fddd-in-practice","09.software-engineering\u002F11.ddd-in-practice",{"title":3243,"icon":943,"path":3244,"stem":3245,"children":3246,"page":59},"DDD","\u002Fddd","10.ddd",[3247,3251,3255,3259,3263,3267,3271,3275,3279,3283,3287,3291,3295],{"title":3248,"path":3249,"stem":3250},"Аналіз предметної області","\u002Fddd\u002Fdomain-analysis","10.ddd\u002F01.domain-analysis",{"title":3252,"path":3253,"stem":3254},"Експертні знання про предметну область","\u002Fddd\u002Fdomain-expert-knowledge","10.ddd\u002F02.domain-expert-knowledge",{"title":3256,"path":3257,"stem":3258},"Як осмислити складність предметної області","\u002Fddd\u002Fmanaging-domain-complexity","10.ddd\u002F03.managing-domain-complexity",{"title":3260,"path":3261,"stem":3262},"Інтеграція обмежених контекстів","\u002Fddd\u002Fbounded-context-integration","10.ddd\u002F04.bounded-context-integration",{"title":3264,"path":3265,"stem":3266},"Реалізація простої бізнес-логіки","\u002Fddd\u002Fsimple-business-logic","10.ddd\u002F05.simple-business-logic",{"title":3268,"path":3269,"stem":3270},"Обробка складної бізнес-логіки","\u002Fddd\u002Fcomplex-business-logic","10.ddd\u002F06.complex-business-logic",{"title":3272,"path":3273,"stem":3274},"Моделювання фактора часу","\u002Fddd\u002Ftime-modeling","10.ddd\u002F07.time-modeling",{"title":3276,"path":3277,"stem":3278},"Глава 8. Архітектурні Патерни","\u002Fddd\u002Farchitectural-patterns","10.ddd\u002F08.architectural-patterns",{"title":3280,"path":3281,"stem":3282},"Глава 9. Патерни Взаємодії","\u002Fddd\u002Finteraction-patterns","10.ddd\u002F09.interaction-patterns",{"title":3284,"path":3285,"stem":3286},"Глава 10. Проектні Евристики","\u002Fddd\u002Fdesign-heuristics","10.ddd\u002F10.design-heuristics",{"title":3288,"path":3289,"stem":3290},"Глава 11. Еволюція Проектних Рішень","\u002Fddd\u002Fevolution-of-design-decisions","10.ddd\u002F11.evolution-of-design-decisions",{"title":3292,"path":3293,"stem":3294},"Глава 12. EventStorming","\u002Fddd\u002Fevent-storming","10.ddd\u002F12.event-storming",{"title":3296,"path":3297,"stem":3298},"Глава 13. DDD на Практиці","\u002Fddd\u002Fddd-in-practice","10.ddd\u002F13.ddd-in-practice",{"title":3300,"icon":3301,"path":3302,"stem":3303,"children":3304,"page":59},"Media Streaming","i-lucide-video","\u002Fmedia-streaming","11.media-streaming",[3305,3309,3313,3317,3321,3325,3329],{"title":3306,"path":3307,"stem":3308},"01. Магія Стрімінгу: Що відбувається, коли ви натискаєте \"Play\"","\u002Fmedia-streaming\u002Fintroduction","11.media-streaming\u002F01.introduction",{"title":3310,"path":3311,"stem":3312},"02. Анатомія Медіа: Кодеки, Контейнери та Стиснення","\u002Fmedia-streaming\u002Faudio-video-anatomy","11.media-streaming\u002F02.audio-video-anatomy",{"title":3314,"path":3315,"stem":3316},"03. The Gym: FFmpeg Deep Dive","\u002Fmedia-streaming\u002Fffmpeg-gym","11.media-streaming\u002F03.ffmpeg-gym",{"title":3318,"path":3319,"stem":3320},"04. HLS Protocol: HTTP Live Streaming у Деталях","\u002Fmedia-streaming\u002Fhls-protocol","11.media-streaming\u002F04.hls-protocol",{"title":3322,"path":3323,"stem":3324},"05. DASH Protocol: Відкритий Стандарт","\u002Fmedia-streaming\u002Fdash-protocol","11.media-streaming\u002F05.dash-protocol",{"title":3326,"path":3327,"stem":3328},"06. Масштабування: CDN та Adaptive Bitrate","\u002Fmedia-streaming\u002Fcdn-and-adaptive-bitrate","11.media-streaming\u002F06.cdn-and-adaptive-bitrate",{"title":3330,"path":3331,"stem":3332},"07. Війна із Затримкою (Latency)","\u002Fmedia-streaming\u002Frealtime-latency","11.media-streaming\u002F07.realtime-latency",{"title":3334,"icon":3335,"path":3336,"stem":3337,"children":3338,"page":59},"HTML & CSS","i-devicon-html5","\u002Fhtml-css","12.html-css",[3339,3343,3347,3351,3355,3359,3363,3367,3371,3375,3379,3383,3387,3391,3395,3399,3403,3407,3411,3415,3419,3423,3427,3431,3435,3439,3443,3447,3451,3455],{"title":3340,"path":3341,"stem":3342},"Вступ до HTML. Структура документа","\u002Fhtml-css\u002Fintro-html-structure","12.html-css\u002F01.intro-html-structure",{"title":3344,"path":3345,"stem":3346},"Форматування тексту в HTML","\u002Fhtml-css\u002Fhtml-text-formatting","12.html-css\u002F02.html-text-formatting",{"title":3348,"path":3349,"stem":3350},"Посилання та зображення в HTML","\u002Fhtml-css\u002Fhtml-links-images","12.html-css\u002F03.html-links-images",{"title":3352,"path":3353,"stem":3354},"Списки та таблиці в HTML","\u002Fhtml-css\u002Fhtml-lists-tables","12.html-css\u002F04.html-lists-tables",{"title":3356,"path":3357,"stem":3358},"Форми в HTML","\u002Fhtml-css\u002Fhtml-forms","12.html-css\u002F05.html-forms",{"title":3360,"path":3361,"stem":3362},"Семантичні елементи HTML5","\u002Fhtml-css\u002Fhtml-semantic-elements","12.html-css\u002F06.html-semantic-elements",{"title":3364,"path":3365,"stem":3366},"Мультимедіа та розширені елементи HTML","\u002Fhtml-css\u002Fhtml-multimedia-advanced","12.html-css\u002F07.html-multimedia-advanced",{"title":3368,"path":3369,"stem":3370},"Мікророзмітка та SEO в HTML","\u002Fhtml-css\u002Fhtml-microdata-seo","12.html-css\u002F08.html-microdata-seo",{"title":3372,"path":3373,"stem":3374},"Вступ до CSS. Селектори та специфічність","\u002Fhtml-css\u002Fcss-intro-selectors","12.html-css\u002F09.css-intro-selectors",{"title":3376,"path":3377,"stem":3378},"Блокова модель CSS. Відступи. Box Sizing","\u002Fhtml-css\u002Fcss-box-model","12.html-css\u002F10.css-box-model",{"title":3380,"path":3381,"stem":3382},"Розміри у CSS: повний довідник одиниць і ключових слів","\u002Fhtml-css\u002F10a.css-sizing","12.html-css\u002F10a.css-sizing",{"title":3384,"path":3385,"stem":3386},"Типографіка в CSS. Шрифти та текст","\u002Fhtml-css\u002Fcss-typography","12.html-css\u002F11.css-typography",{"title":3388,"path":3389,"stem":3390},"Кольори та фони в CSS","\u002Fhtml-css\u002Fcss-colors-backgrounds","12.html-css\u002F12.css-colors-backgrounds",{"title":3392,"path":3393,"stem":3394},"Тіні та фільтри в CSS","\u002Fhtml-css\u002F12b.css-shadows-filters","12.html-css\u002F12b.css-shadows-filters",{"title":3396,"path":3397,"stem":3398},"CSS Flexbox: Фундамент гнучких макетів","\u002Fhtml-css\u002Fcss-flexbox-fundamentals","12.html-css\u002F13.css-flexbox-fundamentals",{"title":3400,"path":3401,"stem":3402},"CSS Flexbox: Вирівнювання та Позиціонування","\u002Fhtml-css\u002Fcss-flexbox-alignment-sizing-and-patterns","12.html-css\u002F14.css-flexbox-alignment-sizing-and-patterns",{"title":3404,"path":3405,"stem":3406},"CSS Grid. Двовимірний макет. Частина 1","\u002Fhtml-css\u002Fcss-layout-grid","12.html-css\u002F15.css-layout-grid",{"title":3408,"path":3409,"stem":3410},"CSS Grid. Двовимірний макет. Частина 2","\u002Fhtml-css\u002Fcss-layout-grid-advanced","12.html-css\u002F16.css-layout-grid-advanced",{"title":3412,"path":3413,"stem":3414},"Позиціонування в CSS. Z-index. Stacking Context","\u002Fhtml-css\u002Fcss-positioning","12.html-css\u002F17.css-positioning",{"title":3416,"path":3417,"stem":3418},"CSS Анімації та Переходи","\u002Fhtml-css\u002Fcss-animations-transitions","12.html-css\u002F18.css-animations-transitions",{"title":3420,"path":3421,"stem":3422},"Адаптивний дизайн. Media Queries. Частина 1","\u002Fhtml-css\u002Fcss-responsive-media-queries","12.html-css\u002F19.css-responsive-media-queries",{"title":3424,"path":3425,"stem":3426},"Адаптивний дизайн. Частина 2: clamp(), Container Queries, @layer","\u002Fhtml-css\u002Fcss-responsive-advanced","12.html-css\u002F20.css-responsive-advanced",{"title":3428,"path":3429,"stem":3430},"CSS Custom Properties. Методології. Сучасний CSS","\u002Fhtml-css\u002Fcss-variables-methodologies","12.html-css\u002F21.css-variables-methodologies",{"title":3432,"path":3433,"stem":3434},"Сучасний CSS 2023–2025: Нові можливості","\u002Fhtml-css\u002Fcss-modern-features","12.html-css\u002F22.css-modern-features",{"title":3436,"path":3437,"stem":3438},"CSS Nesting, @layer, @scope та @property: нативний препроцесор","\u002Fhtml-css\u002F22a.css-nesting-modern-syntax","12.html-css\u002F22a.css-nesting-modern-syntax",{"title":3440,"path":3441,"stem":3442},"CSS для форм та інтерактивних станів","\u002Fhtml-css\u002Fcss-forms-interactive-states","12.html-css\u002F23.css-forms-interactive-states",{"title":3444,"path":3445,"stem":3446},"Доступність у CSS (CSS Accessibility)","\u002Fhtml-css\u002Fcss-accessibility","12.html-css\u002F24.css-accessibility",{"title":3448,"path":3449,"stem":3450},"CSS-функції та сучасні sizing primitives","\u002Fhtml-css\u002Fcss-functions-sizing","12.html-css\u002F25.css-functions-sizing",{"title":3452,"path":3453,"stem":3454},"Rendering Pipeline і CSS Performance","\u002Fhtml-css\u002Fcss-rendering-performance","12.html-css\u002F26.css-rendering-performance",{"title":3456,"path":3457,"stem":3458},"CSS Best Practices: типові ситуації та правильні рішення","\u002Fhtml-css\u002Fcss-best-practices","12.html-css\u002F27.css-best-practices",{"title":3460,"path":3461,"stem":3462,"children":3463,"page":59},"AWS","\u002Faws","13.aws",[3464,3468,3472,3476,3480,3484,3488,3492,3496,3500,3504,3508,3512,3516,3520,3524,3528,3532],{"title":3465,"path":3466,"stem":3467},"Реєстрація AWS акаунту та студентські програми","\u002Faws\u002Faccount-registration","13.aws\u002F00.account-registration",{"title":3469,"path":3470,"stem":3471},"Вступ до хмарних обчислень та AWS","\u002Faws\u002Fintroduction-to-cloud","13.aws\u002F01.introduction-to-cloud",{"title":3473,"path":3474,"stem":3475},"AWS IAM — Identity and Access Management","\u002Faws\u002Fiam","13.aws\u002F02.iam",{"title":3477,"path":3478,"stem":3479},"AWS IAM CLI — Довідник команд","\u002Faws\u002F02a.iam-doc","13.aws\u002F02a.iam-doc",{"title":3481,"path":3482,"stem":3483},"Docker та контейнеризація в AWS — ECR, ECS та Fargate","\u002Faws\u002Fdocker-ecs","13.aws\u002F03.docker-ecs",{"title":3485,"path":3486,"stem":3487},"AWS ECR \u002F ECS CLI — Довідник команд","\u002Faws\u002F03a.docker-ecs-doc","13.aws\u002F03a.docker-ecs-doc",{"title":3489,"path":3490,"stem":3491},"Amazon EC2 — Elastic Compute Cloud","\u002Faws\u002Fec2","13.aws\u002F04.ec2",{"title":3493,"path":3494,"stem":3495},"AWS EC2 CLI — Довідник команд","\u002Faws\u002F04a.ec2-doc","13.aws\u002F04a.ec2-doc",{"title":3497,"path":3498,"stem":3499},"Elastic Load Balancing та Auto Scaling","\u002Faws\u002Falb-asg","13.aws\u002F05.alb-asg",{"title":3501,"path":3502,"stem":3503},"Amazon S3 — Simple Storage Service","\u002Faws\u002Fs3","13.aws\u002F06.s3",{"title":3505,"path":3506,"stem":3507},"Amazon CloudFront — Content Delivery Network","\u002Faws\u002Fcloudfront","13.aws\u002F07.cloudfront",{"title":3509,"path":3510,"stem":3511},"Amazon RDS — Relational Database Service","\u002Faws\u002Frds","13.aws\u002F08.rds",{"title":3513,"path":3514,"stem":3515},"Amazon DynamoDB — NoSQL Database","\u002Faws\u002Fdynamodb","13.aws\u002F09.dynamodb",{"title":3517,"path":3518,"stem":3519},"AWS Lambda та Serverless Compute","\u002Faws\u002Flambda","13.aws\u002F10.lambda",{"title":3521,"path":3522,"stem":3523},"Amazon Bedrock - Foundation Models, RAG та Agents","\u002Faws\u002Fbedrock","13.aws\u002F22.bedrock",{"title":3525,"path":3526,"stem":3527},"Amazon Rekognition - Комп'ютерний зір","\u002Faws\u002Frekognition","13.aws\u002F23.rekognition",{"title":3529,"path":3530,"stem":3531},"Amazon Textract - Інтелектуальний аналіз документів","\u002Faws\u002Ftextract","13.aws\u002F24.textract",{"title":3533,"path":3534,"stem":3535},"Amazon Polly, Transcribe, Comprehend та Translate","\u002Faws\u002Faudio-nlp-services","13.aws\u002F25.audio-nlp-services",{"title":3537,"path":3538,"stem":3539,"children":3540,"page":59},"Ai Development","\u002Fai-development","14.ai-development",[3541],{"title":3542,"path":3543,"stem":3544,"children":3545,"page":59},"Foundations","\u002Fai-development\u002Ffoundations","14.ai-development\u002F00.foundations",[3546],{"title":3547,"path":3548,"stem":3549},"Модуль 0.1. Що таке Large Language Model (LLM)","\u002Fai-development\u002Ffoundations\u002Fwhat-is-llm","14.ai-development\u002F00.foundations\u002F01.what-is-llm",{"title":3551,"path":3552,"stem":3553,"children":3554,"page":59},"React Native","\u002Freact-native","15.react-native",[3555,3576],{"title":3556,"path":3557,"stem":3558,"children":3559,"page":59},"Version1","\u002Freact-native\u002Fversion1","15.react-native\u002Fversion1",[3560,3564,3568,3572],{"title":3561,"path":3562,"stem":3563},"Що таке React Native","\u002Freact-native\u002Fversion1\u002Fwhat-is-react-native","15.react-native\u002Fversion1\u002F01.what-is-react-native",{"title":3565,"path":3566,"stem":3567},"Як влаштований React Native «під капотом»","\u002Freact-native\u002Fversion1\u002Freact-native-architecture","15.react-native\u002Fversion1\u002F02.react-native-architecture",{"title":3569,"path":3570,"stem":3571},"Від React до React Native: ключові відмінності","\u002Freact-native\u002Fversion1\u002Freact-native-vs-react","15.react-native\u002Fversion1\u002F03.react-native-vs-react",{"title":3573,"path":3574,"stem":3575},"View та Text — фундаментальні будівельні блоки","\u002Freact-native\u002Fversion1\u002Fview-and-text","15.react-native\u002Fversion1\u002F04.view-and-text",{"title":3577,"path":3578,"stem":3579,"children":3580,"page":59},"Version2","\u002Freact-native\u002Fversion2","15.react-native\u002Fversion2",[3581,3585,3589,3593,3597,3601,3605,3609,3613,3617,3621,3625,3629,3633,3637,3641,3645,3649,3653,3657,3661,3665,3669,3673,3677,3681,3685],{"title":3582,"path":3583,"stem":3584},"React Native — навіщо він потрібен","\u002Freact-native\u002Fversion2\u002Fwhy-react-native","15.react-native\u002Fversion2\u002F01.why-react-native",{"title":3586,"path":3587,"stem":3588},"Налаштування середовища розробки","\u002Freact-native\u002Fversion2\u002Fenvironment-setup","15.react-native\u002Fversion2\u002F02.environment-setup",{"title":3590,"path":3591,"stem":3592},"Expo і класичний React Native — два шляхи одного фреймворку","\u002Freact-native\u002Fversion2\u002Fexpo-vs-cli-landscape","15.react-native\u002Fversion2\u002F03.expo-vs-cli-landscape",{"title":3594,"path":3595,"stem":3596},"Середовище Expo — перший запуск","\u002Freact-native\u002Fversion2\u002Fexpo-setup-and-tooling","15.react-native\u002Fversion2\u002F04.expo-setup-and-tooling",{"title":3598,"path":3599,"stem":3600},"Структура проєкту та перші UI-примітиви","\u002Freact-native\u002Fversion2\u002Fproject-structure-and-conventions","15.react-native\u002Fversion2\u002F05.project-structure-and-conventions",{"title":3602,"path":3603,"stem":3604},"Базові компоненти React Native","\u002Freact-native\u002Fversion2\u002Fcore-components","15.react-native\u002Fversion2\u002F06.core-components",{"title":3606,"path":3607,"stem":3608},"Flexbox і layout у React Native","\u002Freact-native\u002Fversion2\u002Fflexbox-and-layout","15.react-native\u002Fversion2\u002F07.flexbox-and-layout",{"title":3610,"path":3611,"stem":3612},"StyleSheet і теми (light \u002F dark)","\u002Freact-native\u002Fversion2\u002Fstylesheet-and-theming","15.react-native\u002Fversion2\u002F08.stylesheet-and-theming",{"title":3614,"path":3615,"stem":3616},"Списки та віртуалізація","\u002Freact-native\u002Fversion2\u002Flists-and-virtualization","15.react-native\u002Fversion2\u002F09.lists-and-virtualization",{"title":3618,"path":3619,"stem":3620},"Форми, ввід і валідація","\u002Freact-native\u002Fversion2\u002Fforms-input-validation","15.react-native\u002Fversion2\u002F10.forms-input-validation",{"title":3622,"path":3623,"stem":3624},"Основи Expo Router","\u002Freact-native\u002Fversion2\u002Fexpo-router-basics","15.react-native\u002Fversion2\u002F11.expo-router-basics",{"title":3626,"path":3627,"stem":3628},"Вкладені навігатори та модалки","\u002Freact-native\u002Fversion2\u002Fnested-navigators-and-modals","15.react-native\u002Fversion2\u002F12.nested-navigators-and-modals",{"title":3630,"path":3631,"stem":3632},"Deep linking і параметри маршрутів","\u002Freact-native\u002Fversion2\u002Fdeep-linking-and-params","15.react-native\u002Fversion2\u002F13.deep-linking-and-params",{"title":3634,"path":3635,"stem":3636},"Робота з мережею та життєвий цикл застосунку","\u002Freact-native\u002Fversion2\u002Fnetworking-and-app-lifecycle","15.react-native\u002Fversion2\u002F14.networking-and-app-lifecycle",{"title":3638,"path":3639,"stem":3640},"Redux Toolkit на мобільних платформах","\u002Freact-native\u002Fversion2\u002Fredux-toolkit-on-mobile","15.react-native\u002Fversion2\u002F15.redux-toolkit-on-mobile",{"title":3642,"path":3643,"stem":3644},"RTK Query на мобільних платформах","\u002Freact-native\u002Fversion2\u002Frtk-query-mobile","15.react-native\u002Fversion2\u002F16.rtk-query-mobile",{"title":3646,"path":3647,"stem":3648},"Автентифікація та Безпечне Зберігання","\u002Freact-native\u002Fversion2\u002Fauth-secure-storage","15.react-native\u002Fversion2\u002F18.auth-secure-storage",{"title":3650,"path":3651,"stem":3652},"Локальне сховище — AsyncStorage, MMKV, SQLite","\u002Freact-native\u002Fversion2\u002Flocal-storage-mmkv-sqlite","15.react-native\u002Fversion2\u002F19.local-storage-mmkv-sqlite",{"title":3654,"path":3655,"stem":3656},"Офлайн-First і синхронізація","\u002Freact-native\u002Fversion2\u002Foffline-first-sync","15.react-native\u002Fversion2\u002F20.offline-first-sync",{"title":3658,"path":3659,"stem":3660},"Камера, медіа та файлова система","\u002Freact-native\u002Fversion2\u002Fcamera-media-filesystem","15.react-native\u002Fversion2\u002F21.camera-media-filesystem",{"title":3662,"path":3663,"stem":3664},"Карти та геолокація","\u002Freact-native\u002Fversion2\u002Fmaps-and-location","15.react-native\u002Fversion2\u002F22.maps-and-location",{"title":3666,"path":3667,"stem":3668},"Жести та дотики","\u002Freact-native\u002Fversion2\u002Fgestures-and-touch","15.react-native\u002Fversion2\u002F23.gestures-and-touch",{"title":3670,"path":3671,"stem":3672},"Анімації з Reanimated","\u002Freact-native\u002Fversion2\u002Freanimated-animations","15.react-native\u002Fversion2\u002F24.reanimated-animations",{"title":3674,"path":3675,"stem":3676},"Push і локальні сповіщення","\u002Freact-native\u002Fversion2\u002Fpush-and-local-notifications","15.react-native\u002Fversion2\u002F25.push-and-local-notifications",{"title":3678,"path":3679,"stem":3680},"Інтернаціоналізація та доступність","\u002Freact-native\u002Fversion2\u002Faccessibility-and-i18n","15.react-native\u002Fversion2\u002F26.accessibility-and-i18n",{"title":3682,"path":3683,"stem":3684},"EAS Build та профілі збірки","\u002Freact-native\u002Fversion2\u002Feas-build-and-profiles","15.react-native\u002Fversion2\u002F29.eas-build-and-profiles",{"title":3686,"path":3687,"stem":3688},"Публікація в App Store та Google Play","\u002Freact-native\u002Fversion2\u002Fapp-store-play-release","15.react-native\u002Fversion2\u002F30.app-store-play-release",{"title":3690,"path":3691,"stem":3692,"children":3693,"page":59},"Ai Python","\u002Fai-python","16.ai-python",[3694,3703,3712,3721,3750,3776,3801,3834,3851,3864,3873,3886,3895,3916,3929,3950],{"title":3695,"path":3696,"stem":3697,"children":3698,"page":59},"Intro To Ai","\u002Fai-python\u002Fintro-to-ai","16.ai-python\u002F01.intro-to-ai",[3699],{"title":3700,"path":3701,"stem":3702},"Вступ до штучного інтелекту та машинного навчання","\u002Fai-python\u002Fintro-to-ai\u002Fintro-to-ai","16.ai-python\u002F01.intro-to-ai\u002F01.intro-to-ai",{"title":3704,"path":3705,"stem":3706,"children":3707,"page":59},"Jupyter Notebook","\u002Fai-python\u002Fjupyter-notebook","16.ai-python\u002F02.jupyter-notebook",[3708],{"title":3709,"path":3710,"stem":3711},"Знайомство з Jupyter Notebook та JupyterLab","\u002Fai-python\u002Fjupyter-notebook\u002Fjupyter-notebook","16.ai-python\u002F02.jupyter-notebook\u002F02.jupyter-notebook",{"title":3713,"path":3714,"stem":3715,"children":3716,"page":59},"Numpy Pandas","\u002Fai-python\u002Fnumpy-pandas","16.ai-python\u002F03.numpy-pandas",[3717],{"title":3718,"path":3719,"stem":3720},"Робота з даними з використанням NumPy і pandas","\u002Fai-python\u002Fnumpy-pandas\u002Fnumpy-pandas","16.ai-python\u002F03.numpy-pandas\u002F03.numpy-pandas",{"title":3722,"path":3723,"stem":3724,"children":3725,"page":59},"Statistics Basics","\u002Fai-python\u002Fstatistics-basics","16.ai-python\u002F04.statistics-basics",[3726,3730,3734,3738,3742,3746],{"title":3727,"path":3728,"stem":3729},"Випадкові величини та їх типи","\u002Fai-python\u002Fstatistics-basics\u002Frandom-variables","16.ai-python\u002F04.statistics-basics\u002F01.random-variables",{"title":3731,"path":3732,"stem":3733},"Міри центральної тенденції","\u002Fai-python\u002Fstatistics-basics\u002Fcentral-tendency","16.ai-python\u002F04.statistics-basics\u002F02.central-tendency",{"title":3735,"path":3736,"stem":3737},"Міри варіації (розсіювання)","\u002Fai-python\u002Fstatistics-basics\u002Fvariability","16.ai-python\u002F04.statistics-basics\u002F03.variability",{"title":3739,"path":3740,"stem":3741},"Розподіли випадкових величин","\u002Fai-python\u002Fstatistics-basics\u002Fdistributions","16.ai-python\u002F04.statistics-basics\u002F04.distributions",{"title":3743,"path":3744,"stem":3745},"Кореляція та взаємозв'язки","\u002Fai-python\u002Fstatistics-basics\u002Fcorrelation","16.ai-python\u002F04.statistics-basics\u002F05.correlation",{"title":3747,"path":3748,"stem":3749},"Викиди та аномалії","\u002Fai-python\u002Fstatistics-basics\u002Foutliers","16.ai-python\u002F04.statistics-basics\u002F06.outliers",{"title":3751,"path":3752,"stem":3753,"children":3754},"Візуалізація даних за допомогою matplotlib","\u002Fai-python\u002Fdata-visualization","16.ai-python\u002F05.data-visualization\u002Findex",[3755,3756,3760,3764,3768,3772],{"title":3751,"path":3752,"stem":3753},{"title":3757,"path":3758,"stem":3759},"Основи matplotlib — Figure, Axes та перший графік","\u002Fai-python\u002Fdata-visualization\u002Fmatplotlib-basics","16.ai-python\u002F05.data-visualization\u002F01.matplotlib-basics",{"title":3761,"path":3762,"stem":3763},"Візуалізація розподілів — гістограми та box plots","\u002Fai-python\u002Fdata-visualization\u002Fdistributions","16.ai-python\u002F05.data-visualization\u002F02.distributions",{"title":3765,"path":3766,"stem":3767},"Візуалізація залежностей — scatter plots та кореляція","\u002Fai-python\u002Fdata-visualization\u002Frelationships","16.ai-python\u002F05.data-visualization\u002F03.relationships",{"title":3769,"path":3770,"stem":3771},"Візуалізація категоріальних даних — bar charts та pie charts","\u002Fai-python\u002Fdata-visualization\u002Fcategorical","16.ai-python\u002F05.data-visualization\u002F04.categorical",{"title":3773,"path":3774,"stem":3775},"Композиції та стилізація — subplots та багатопанельні дашборди","\u002Fai-python\u002Fdata-visualization\u002Fsubplots-styling","16.ai-python\u002F05.data-visualization\u002F05.subplots-styling",{"title":3777,"path":3778,"stem":3779,"children":3780,"page":59},"Linear Regression","\u002Fai-python\u002Flinear-regression","16.ai-python\u002F06.linear-regression",[3781,3785,3789,3793,3797],{"title":3782,"path":3783,"stem":3784},"Регресійна задача та лінійна регресія з однією змінною","\u002Fai-python\u002Flinear-regression\u002Fregression-task","16.ai-python\u002F06.linear-regression\u002F01.regression-task",{"title":3786,"path":3787,"stem":3788},"Метрики якості регресії — як оцінити модель","\u002Fai-python\u002Flinear-regression\u002Fquality-metrics","16.ai-python\u002F06.linear-regression\u002F02.quality-metrics",{"title":3790,"path":3791,"stem":3792},"Градієнтний спуск — як модель навчається","\u002Fai-python\u002Flinear-regression\u002Fgradient-descent","16.ai-python\u002F06.linear-regression\u002F03.gradient-descent",{"title":3794,"path":3795,"stem":3796},"Множинна лінійна регресія — модель з багатьма ознаками","\u002Fai-python\u002Flinear-regression\u002Fmultiple-regression","16.ai-python\u002F06.linear-regression\u002F04.multiple-regression",{"title":3798,"path":3799,"stem":3800},"Практичні завдання та резюме модуля","\u002Fai-python\u002Flinear-regression\u002Fpractice","16.ai-python\u002F06.linear-regression\u002F05.practice",{"title":3802,"path":3803,"stem":3804,"children":3805,"page":59},"Practical Regression","\u002Fai-python\u002Fpractical-regression","16.ai-python\u002F07.practical-regression",[3806,3810,3814,3818,3822,3826,3830],{"title":3807,"path":3808,"stem":3809},"Знайомство з scikit-learn","\u002Fai-python\u002Fpractical-regression\u002Fintro-scikit-learn","16.ai-python\u002F07.practical-regression\u002F01.intro-scikit-learn",{"title":3811,"path":3812,"stem":3813},"Exploratory Data Analysis датасету Housing Prices","\u002Fai-python\u002Fpractical-regression\u002Fhousing-dataset-eda","16.ai-python\u002F07.practical-regression\u002F02.housing-dataset-eda",{"title":3815,"path":3816,"stem":3817},"Попередня обробка даних (Data Preprocessing)","\u002Fai-python\u002Fpractical-regression\u002Fdata-preprocessing","16.ai-python\u002F07.practical-regression\u002F03.data-preprocessing",{"title":3819,"path":3820,"stem":3821},"Train\u002FTest Split та перша повноцінна модель","\u002Fai-python\u002Fpractical-regression\u002Ftrain-test-split","16.ai-python\u002F07.practical-regression\u002F04.train-test-split",{"title":3823,"path":3824,"stem":3825},"Перенавчання та недонавчання","\u002Fai-python\u002Fpractical-regression\u002Foverfitting-underfitting","16.ai-python\u002F07.practical-regression\u002F05.overfitting-underfitting",{"title":3827,"path":3828,"stem":3829},"Крос-валідація (Cross-Validation)","\u002Fai-python\u002Fpractical-regression\u002Fcross-validation","16.ai-python\u002F07.practical-regression\u002F06.cross-validation",{"title":3831,"path":3832,"stem":3833},"Гіперпараметри та їх оптимізація","\u002Fai-python\u002Fpractical-regression\u002Fhyperparameter-tuning","16.ai-python\u002F07.practical-regression\u002F07.hyperparameter-tuning",{"title":3835,"path":3836,"stem":3837,"children":3838,"page":59},"Polynomial Regression","\u002Fai-python\u002Fpolynomial-regression","16.ai-python\u002F08.polynomial-regression",[3839,3843,3847],{"title":3840,"path":3841,"stem":3842},"Нелінійні залежності та поліноміальна регресія","\u002Fai-python\u002Fpolynomial-regression\u002Fnonlinear-patterns","16.ai-python\u002F08.polynomial-regression\u002F01.nonlinear-patterns",{"title":3844,"path":3845,"stem":3846},"Регуляризація в регресії — Ridge та Lasso","\u002Fai-python\u002Fpolynomial-regression\u002Fregularization-methods","16.ai-python\u002F08.polynomial-regression\u002F02.regularization-methods",{"title":3848,"path":3849,"stem":3850},"Практика — поліноміальна регресія та регуляризація на Housing Prices","\u002Fai-python\u002Fpolynomial-regression\u002Fhousing-prices-practice","16.ai-python\u002F08.polynomial-regression\u002F03.housing-prices-practice",{"title":3852,"path":3853,"stem":3854,"children":3855,"page":59},"Decision Trees Random Forest","\u002Fai-python\u002Fdecision-trees-random-forest","16.ai-python\u002F09.decision-trees-random-forest",[3856,3860],{"title":3857,"path":3858,"stem":3859},"Дерева рішень — моделі з прозорою та зрозумілою логікою","\u002Fai-python\u002Fdecision-trees-random-forest\u002Fdecision-trees","16.ai-python\u002F09.decision-trees-random-forest\u002F01.decision-trees",{"title":3861,"path":3862,"stem":3863},"Random Forest — ансамблі дерев рішень","\u002Fai-python\u002Fdecision-trees-random-forest\u002Frandom-forest","16.ai-python\u002F09.decision-trees-random-forest\u002F02.random-forest",{"title":3865,"path":3866,"stem":3867,"children":3868,"page":59},"Gradient Boosting","\u002Fai-python\u002Fgradient-boosting","16.ai-python\u002F10.gradient-boosting",[3869],{"title":3870,"path":3871,"stem":3872},"Градієнтний бустинг та XGBoost — послідовне виправлення помилок","\u002Fai-python\u002Fgradient-boosting\u002Fgradient-boosting-xgboost","16.ai-python\u002F10.gradient-boosting\u002F01.gradient-boosting-xgboost",{"title":3874,"path":3875,"stem":3876,"children":3877,"page":59},"Logistic Regression Classification","\u002Fai-python\u002Flogistic-regression-classification","16.ai-python\u002F11.logistic-regression-classification",[3878,3882],{"title":3879,"path":3880,"stem":3881},"Основи класифікації та логістична регресія","\u002Fai-python\u002Flogistic-regression-classification\u002Fclassification-basics","16.ai-python\u002F11.logistic-regression-classification\u002F01.classification-basics",{"title":3883,"path":3884,"stem":3885},"Метрики якості класифікації","\u002Fai-python\u002Flogistic-regression-classification\u002Fclassification-metrics","16.ai-python\u002F11.logistic-regression-classification\u002F02.classification-metrics",{"title":3887,"path":3888,"stem":3889,"children":3890,"page":59},"Neural Networks Basics","\u002Fai-python\u002Fneural-networks-basics","16.ai-python\u002F12.neural-networks-basics",[3891],{"title":3892,"path":3893,"stem":3894},"Вступ до нейронних мереж — від персептрона до багатошарових мереж","\u002Fai-python\u002Fneural-networks-basics\u002Fperceptron-to-mlp","16.ai-python\u002F12.neural-networks-basics\u002F01.perceptron-to-mlp",{"title":3896,"path":3897,"stem":3898,"children":3899,"page":59},"Pytorch Intro","\u002Fai-python\u002Fpytorch-intro","16.ai-python\u002F13.pytorch-intro",[3900,3904,3908,3912],{"title":3901,"path":3902,"stem":3903},"Тензори та автоматичне диференціювання в PyTorch","\u002Fai-python\u002Fpytorch-intro\u002Ftensors-and-autograd","16.ai-python\u002F13.pytorch-intro\u002F01.tensors-and-autograd",{"title":3905,"path":3906,"stem":3907},"Побудова та тренування нейронних мереж у PyTorch","\u002Fai-python\u002Fpytorch-intro\u002Fbuilding-and-training","16.ai-python\u002F13.pytorch-intro\u002F02.building-and-training",{"title":3909,"path":3910,"stem":3911},"Робота з даними та регуляризація в PyTorch","\u002Fai-python\u002Fpytorch-intro\u002Fdata-and-regularization","16.ai-python\u002F13.pytorch-intro\u002F03.data-and-regularization",{"title":3913,"path":3914,"stem":3915},"Просунуті теми PyTorch — GPU, оптимізація та deployment","\u002Fai-python\u002Fpytorch-intro\u002Fadvanced-topics","16.ai-python\u002F13.pytorch-intro\u002F04.advanced-topics",{"title":3917,"path":3918,"stem":3919,"children":3920,"page":59},"Activation Functions Heart Disease","\u002Fai-python\u002Factivation-functions-heart-disease","16.ai-python\u002F14.activation-functions-heart-disease",[3921,3925],{"title":3922,"path":3923,"stem":3924},"Функції активації та побудова нейронної мережі для передбачення вад серця","\u002Fai-python\u002Factivation-functions-heart-disease\u002Fheart-disease-prediction","16.ai-python\u002F14.activation-functions-heart-disease\u002F01.heart-disease-prediction",{"title":3926,"path":3927,"stem":3928},"Бонус — Повний приклад Student Performance Prediction","\u002Fai-python\u002Factivation-functions-heart-disease\u002Fstudent-performance-bonus","16.ai-python\u002F14.activation-functions-heart-disease\u002F02.student-performance-bonus",{"title":3930,"path":3931,"stem":3932,"children":3933,"page":59},"Cnn Image Classification","\u002Fai-python\u002Fcnn-image-classification","16.ai-python\u002F15.cnn-image-classification",[3934,3938,3942,3946],{"title":3935,"path":3936,"stem":3937},"Основи згорткових нейронних мереж — чому не MLP?","\u002Fai-python\u002Fcnn-image-classification\u002Fcnn-fundamentals","16.ai-python\u002F15.cnn-image-classification\u002F01.cnn-fundamentals",{"title":3939,"path":3940,"stem":3941},"Практична імплементація CNN для класифікації MNIST","\u002Fai-python\u002Fcnn-image-classification\u002Fmnist-classification","16.ai-python\u002F15.cnn-image-classification\u002F02.mnist-classification",{"title":3943,"path":3944,"stem":3945},"Глибші CNN та аугментація даних для CIFAR-10","\u002Fai-python\u002Fcnn-image-classification\u002Fcifar10-and-data-augmentation","16.ai-python\u002F15.cnn-image-classification\u002F03.cifar10-and-data-augmentation",{"title":3947,"path":3948,"stem":3949},"Transfer Learning та візуалізація внутрішніх представлень CNN","\u002Fai-python\u002Fcnn-image-classification\u002Ftransfer-learning-and-visualization","16.ai-python\u002F15.cnn-image-classification\u002F04.transfer-learning-and-visualization",{"title":3951,"path":3952,"stem":3953,"children":3954,"page":59},"Batching Normalization Deep Networks","\u002Fai-python\u002Fbatching-normalization-deep-networks","16.ai-python\u002F16.batching-normalization-deep-networks",[3955,3959,3963,3967,3971,3975,3979],{"title":3956,"path":3957,"stem":3958},"Mini-batch Gradient Descent та ефективна обробка даних","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fmini-batch-gradient-descent","16.ai-python\u002F16.batching-normalization-deep-networks\u002F01.mini-batch-gradient-descent",{"title":3960,"path":3961,"stem":3962},"Ініціалізація ваг — фундамент стабільного навчання","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fweight-initialization","16.ai-python\u002F16.batching-normalization-deep-networks\u002F02.weight-initialization",{"title":3964,"path":3965,"stem":3966},"Batch Normalization — прорив у глибокому навчанні","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fbatch-normalization","16.ai-python\u002F16.batching-normalization-deep-networks\u002F03.batch-normalization",{"title":3968,"path":3969,"stem":3970},"Dropout та комбіновані стратегії регуляризації","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fdropout-and-regularization","16.ai-python\u002F16.batching-normalization-deep-networks\u002F04.dropout-and-regularization",{"title":3972,"path":3973,"stem":3974},"Проєктування глибоких мереж — від теорії до практики","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fdeep-networks-architectures","16.ai-python\u002F16.batching-normalization-deep-networks\u002F05.deep-networks-architectures",{"title":3976,"path":3977,"stem":3978},"Планування learning rate — коли та як зменшувати крок навчання","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling","16.ai-python\u002F16.batching-normalization-deep-networks\u002F06.learning-rate-scheduling",{"title":3980,"path":3981,"stem":3982},"Підсумковий проєкт — побудова сучасного класифікатора зображень","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Ffinal-project-deep-classifier","16.ai-python\u002F16.batching-normalization-deep-networks\u002F07.final-project-deep-classifier",{"title":3984,"icon":658,"path":3985,"stem":3986,"children":3987,"page":59},"Клієнт-серверна архітектура","\u002Fclient-server-architecture","17.client-server-architecture",[3988,3992,3996,4000,4004,4008,4012,4016,4020,4024,4028,4032,4036,4040,4044,4048,4052,4056],{"title":3989,"path":3990,"stem":3991},"Архітектура клієнт-серверних систем та основи Go","\u002Fclient-server-architecture\u002Fclient-server-architecture-and-go","17.client-server-architecture\u002F01.client-server-architecture-and-go",{"title":3993,"path":3994,"stem":3995},"Система типів та модель пам’яті мови Go","\u002Fclient-server-architecture\u002Ftype-system-and-memory-model","17.client-server-architecture\u002F02.type-system-and-memory-model",{"title":3997,"path":3998,"stem":3999},"Інтерфейси та модель конкурентності мови Go","\u002Fclient-server-architecture\u002Finterfaces-and-concurrency-model","17.client-server-architecture\u002F03.interfaces-and-concurrency-model",{"title":4001,"path":4002,"stem":4003},"Сокетне програмування та протокол TCP у Go","\u002Fclient-server-architecture\u002Ftcp-socket-programming","17.client-server-architecture\u002F04.tcp-socket-programming",{"title":4005,"path":4006,"stem":4007},"Протокол UDP та датаграмна передача даних","\u002Fclient-server-architecture\u002Fudp-datagram-transmission","17.client-server-architecture\u002F05.udp-datagram-transmission",{"title":4009,"path":4010,"stem":4011},"Криптографічний захист каналів зв","\u002Fclient-server-architecture\u002Ftls-cryptographic-channel-protection","17.client-server-architecture\u002F06.tls-cryptographic-channel-protection",{"title":4013,"path":4014,"stem":4015},"Прикладні мережеві протоколи DNS та SMTP","\u002Fclient-server-architecture\u002Fdns-smtp-application-protocols","17.client-server-architecture\u002F07.dns-smtp-application-protocols",{"title":4017,"path":4018,"stem":4019},"Протокол HTTP та стандартний вебсервер Go","\u002Fclient-server-architecture\u002Fhttp-protocol-and-web-server","17.client-server-architecture\u002F08.http-protocol-and-web-server",{"title":4021,"path":4022,"stem":4023},"Проєктування REST API та маршрутизація засобами Chi","\u002Fclient-server-architecture\u002Frest-api-design-and-chi-routing","17.client-server-architecture\u002F09.rest-api-design-and-chi-routing",{"title":4025,"path":4026,"stem":4027},"Лекція 10. Шарувата архітектура та конвеєри обробки запитів","\u002Fclient-server-architecture\u002Flayered-architecture-and-middleware-pipelines","17.client-server-architecture\u002F10.layered-architecture-and-middleware-pipelines",{"title":4029,"path":4030,"stem":4031},"Лекція 11. Архітектура та маршрутизація фреймворку Gin","\u002Fclient-server-architecture\u002Fgin-framework-architecture-and-routing","17.client-server-architecture\u002F11.gin-framework-architecture-and-routing",{"title":4033,"path":4034,"stem":4035},"Лекція 12. Валідація даних, безпека та документування у Gin","\u002Fclient-server-architecture\u002Fdata-validation-security-and-documentation-in-gin","17.client-server-architecture\u002F12.data-validation-security-and-documentation-in-gin",{"title":4037,"path":4038,"stem":4039},"Лекція 13. Взаємодія з реляційними СУБД та технології ORM","\u002Fclient-server-architecture\u002Frelational-databases-and-orm","17.client-server-architecture\u002F13.relational-databases-and-orm",{"title":4041,"path":4042,"stem":4043},"Потокова передача даних та протокол WebSocket","\u002Fclient-server-architecture\u002Fstreaming-data-and-websockets","17.client-server-architecture\u002F14.streaming-data-and-websockets",{"title":4045,"path":4046,"stem":4047},"Міжсервісна взаємодія на основі протоколу gRPC","\u002Fclient-server-architecture\u002Fgrpc-inter-service-communication","17.client-server-architecture\u002F15.grpc-inter-service-communication",{"title":4049,"path":4050,"stem":4051},"Асинхронний обмін повідомленнями та протоколи черг","\u002Fclient-server-architecture\u002Fasynchronous-message-exchange-and-queue-protocols","17.client-server-architecture\u002F16.asynchronous-message-exchange-and-queue-protocols",{"title":4053,"path":4054,"stem":4055},"Протоколи потокового медіа та технологія WebRTC","\u002Fclient-server-architecture\u002Fstreaming-media-protocols-and-webrtc","17.client-server-architecture\u002F17.streaming-media-protocols-and-webrtc",{"title":4057,"path":4058,"stem":4059},"Моніторинг, безпека та контейнеризація застосунків","\u002Fclient-server-architecture\u002Fmonitoring-security-and-containerization","17.client-server-architecture\u002F18.monitoring-security-and-containerization",{"title":4061,"icon":2118,"path":4062,"stem":4063,"children":4064,"page":59},"Розробка WEB-застосувань","\u002Fweb-development","18.web-development",[4065,4110,4148,4177,4206,4263,4313,4407,4473,4555,4588,4616,4658,4704,4747],{"title":4066,"icon":658,"path":4067,"stem":4068,"children":4069,"page":59},"Архітектура комп'ютерних мереж та мережеві протоколи","\u002Fweb-development\u002Fnetwork-architecture-and-protocols","18.web-development\u002F01.network-architecture-and-protocols",[4070,4074,4078,4082,4086,4090,4094,4098,4102,4106],{"title":4071,"path":4072,"stem":4073},"Еволюція веброзробки та модель клієнт-сервер","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fweb-evolution-client-server","18.web-development\u002F01.network-architecture-and-protocols\u002F01.web-evolution-client-server",{"title":4075,"path":4076,"stem":4077},"Еталонна модель OSI","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fosi-model","18.web-development\u002F01.network-architecture-and-protocols\u002F02.osi-model",{"title":4079,"path":4080,"stem":4081},"Стек протоколів TCP\u002FIP","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Ftcp-ip-stack","18.web-development\u002F01.network-architecture-and-protocols\u002F03.tcp-ip-stack",{"title":4083,"path":4084,"stem":4085},"IP-адресація, порти та сокети","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fip-addressing-ports-sockets","18.web-development\u002F01.network-architecture-and-protocols\u002F04.ip-addressing-ports-sockets",{"title":4087,"path":4088,"stem":4089},"Протоколи TCP та UDP","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Ftcp-udp-protocols","18.web-development\u002F01.network-architecture-and-protocols\u002F05.tcp-udp-protocols",{"title":4091,"path":4092,"stem":4093},"Система доменних імен DNS","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fdns-system","18.web-development\u002F01.network-architecture-and-protocols\u002F06.dns-system",{"title":4095,"path":4096,"stem":4097},"Протокол SMTP та поштові протоколи","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fsmtp-email-protocols","18.web-development\u002F01.network-architecture-and-protocols\u002F07.smtp-email-protocols",{"title":4099,"path":4100,"stem":4101},"Протокол WebSocket","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fwebsocket-protocol","18.web-development\u002F01.network-architecture-and-protocols\u002F08.websocket-protocol",{"title":4103,"path":4104,"stem":4105},"Протокол SSH","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fssh-protocol","18.web-development\u002F01.network-architecture-and-protocols\u002F09.ssh-protocol",{"title":4107,"path":4108,"stem":4109},"Огляд сучасних серверних технологій","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fmodern-backend-technologies","18.web-development\u002F01.network-architecture-and-protocols\u002F10.modern-backend-technologies",{"title":4111,"icon":4112,"path":4113,"stem":4114,"children":4115,"page":59},"Протокол HTTP та захищена передача даних HTTPS","i-lucide-lock","\u002Fweb-development\u002Fhttp-and-https","18.web-development\u002F02.http-and-https",[4116,4120,4124,4128,4132,4136,4140,4144],{"title":4117,"path":4118,"stem":4119},"Вступ до протоколу HTTP та еволюція веб-технологій","\u002Fweb-development\u002Fhttp-and-https\u002Fintroduction-and-evolution","18.web-development\u002F02.http-and-https\u002F01.introduction-and-evolution",{"title":4121,"path":4122,"stem":4123},"Анатомія HTTP-запиту","\u002Fweb-development\u002Fhttp-and-https\u002Fhttp-request-structure","18.web-development\u002F02.http-and-https\u002F02.http-request-structure",{"title":4125,"path":4126,"stem":4127},"Анатомія HTTP-відповіді","\u002Fweb-development\u002Fhttp-and-https\u002Fhttp-response-structure","18.web-development\u002F02.http-and-https\u002F03.http-response-structure",{"title":4129,"path":4130,"stem":4131},"Методи HTTP та їхня семантика","\u002Fweb-development\u002Fhttp-and-https\u002Fhttp-methods","18.web-development\u002F02.http-and-https\u002F04.http-methods",{"title":4133,"path":4134,"stem":4135},"Коди статусу HTTP та їхнє призначення","\u002Fweb-development\u002Fhttp-and-https\u002Fhttp-status-codes","18.web-development\u002F02.http-and-https\u002F05.http-status-codes",{"title":4137,"path":4138,"stem":4139},"HTTP-заголовки та їхнє призначення","\u002Fweb-development\u002Fhttp-and-https\u002Fhttp-headers","18.web-development\u002F02.http-and-https\u002F06.http-headers",{"title":4141,"path":4142,"stem":4143},"CORS та механізми безпеки HTTP","\u002Fweb-development\u002Fhttp-and-https\u002Fcors-and-security","18.web-development\u002F02.http-and-https\u002F07.cors-and-security",{"title":4145,"path":4146,"stem":4147},"HTTPS та криптографічні основи TLS","\u002Fweb-development\u002Fhttp-and-https\u002Fhttps-and-tls","18.web-development\u002F02.http-and-https\u002F08.https-and-tls",{"title":4149,"icon":2498,"path":4150,"stem":4151,"children":4152,"page":59},"Система типів мови TypeScript","\u002Fweb-development\u002Ftypescript-type-system","18.web-development\u002F03.typescript-type-system",[4153,4157,4161,4165,4169,4173],{"title":4154,"path":4155,"stem":4156},"Знайомство з TypeScript Compiler","\u002Fweb-development\u002Ftypescript-type-system\u002Fintroduction-compiler-config","18.web-development\u002F03.typescript-type-system\u002F01.introduction-compiler-config",{"title":4158,"path":4159,"stem":4160},"Примітивні типи даних: string, number, boolean","\u002Fweb-development\u002Ftypescript-type-system\u002Fprimitive-special-types","18.web-development\u002F03.typescript-type-system\u002F02.primitive-special-types",{"title":4162,"path":4163,"stem":4164},"Масиви, кортежі та об","\u002Fweb-development\u002Ftypescript-type-system\u002Farrays-tuples-objects","18.web-development\u002F03.typescript-type-system\u002F03.arrays-tuples-objects",{"title":4166,"path":4167,"stem":4168},"Псевдоніми типів, Union типи, Intersection типи та літеральні типи","\u002Fweb-development\u002Ftypescript-type-system\u002Funion-intersection-literals","18.web-development\u002F03.typescript-type-system\u002F04.union-intersection-literals",{"title":4170,"path":4171,"stem":4172},"Type Narrowing (звуження типів)","\u002Fweb-development\u002Ftypescript-type-system\u002Ftype-narrowing","18.web-development\u002F03.typescript-type-system\u002F05.type-narrowing",{"title":4174,"path":4175,"stem":4176},"Типізація функцій","\u002Fweb-development\u002Ftypescript-type-system\u002Ffunctions-typing","18.web-development\u002F03.typescript-type-system\u002F06.functions-typing",{"title":4178,"icon":2498,"path":4179,"stem":4180,"children":4181,"page":59},"Розширені засоби мови TypeScript","\u002Fweb-development\u002Ftypescript-advanced","18.web-development\u002F04.typescript-advanced",[4182,4186,4190,4194,4198,4202],{"title":4183,"path":4184,"stem":4185},"Interfaces та Classes","\u002Fweb-development\u002Ftypescript-advanced\u002Finterfaces-classes","18.web-development\u002F04.typescript-advanced\u002F01.interfaces-classes",{"title":4187,"path":4188,"stem":4189},"Основи Generic типів","\u002Fweb-development\u002Ftypescript-advanced\u002Fgenerics-fundamentals","18.web-development\u002F04.typescript-advanced\u002F02.generics-fundamentals",{"title":4191,"path":4192,"stem":4193},"Enums та Decorators","\u002Fweb-development\u002Ftypescript-advanced\u002Fenums-decorators","18.web-development\u002F04.typescript-advanced\u002F03.enums-decorators",{"title":4195,"path":4196,"stem":4197},"Utility Types","\u002Fweb-development\u002Ftypescript-advanced\u002Futility-types","18.web-development\u002F04.typescript-advanced\u002F04.utility-types",{"title":4199,"path":4200,"stem":4201},"Mapped та Conditional Types","\u002Fweb-development\u002Ftypescript-advanced\u002Fmapped-conditional-types","18.web-development\u002F04.typescript-advanced\u002F05.mapped-conditional-types",{"title":4203,"path":4204,"stem":4205},"Модулі та Strict Mode","\u002Fweb-development\u002Ftypescript-advanced\u002Fmodules-strict-mode","18.web-development\u002F04.typescript-advanced\u002F06.modules-strict-mode",{"title":4207,"icon":4208,"path":4209,"stem":4210,"children":4211,"page":59},"Платформа Node.js як середовище виконання","i-devicon-nodejs","\u002Fweb-development\u002Fnodejs-platform","18.web-development\u002F05.nodejs-platform",[4212,4216,4220,4224,4228,4232,4236,4240,4244,4248,4252,4255,4259],{"title":4213,"path":4214,"stem":4215},"Що таке Node.js та його архітектура","\u002Fweb-development\u002Fnodejs-platform\u002Fwhat-is-nodejs","18.web-development\u002F05.nodejs-platform\u002F01.what-is-nodejs",{"title":4217,"path":4218,"stem":4219},"Event Loop — серце Node.js","\u002Fweb-development\u002Fnodejs-platform\u002Fevent-loop","18.web-development\u002F05.nodejs-platform\u002F02.event-loop",{"title":4221,"path":4222,"stem":4223},"Модульні системи: CommonJS vs ES Modules","\u002Fweb-development\u002Fnodejs-platform\u002Fmodule-systems","18.web-development\u002F05.nodejs-platform\u002F03.module-systems",{"title":4225,"path":4226,"stem":4227},"npm та package.json","\u002Fweb-development\u002Fnodejs-platform\u002Fnpm-package-json","18.web-development\u002F05.nodejs-platform\u002F04.npm-package-json",{"title":4229,"path":4230,"stem":4231},"Глобальні об\\","\u002Fweb-development\u002Fnodejs-platform\u002Fglobal-objects","18.web-development\u002F05.nodejs-platform\u002F05.global-objects",{"title":4233,"path":4234,"stem":4235},"Вбудований модуль fs (File System)","\u002Fweb-development\u002Fnodejs-platform\u002Fbuilt-in-modules-fs","18.web-development\u002F05.nodejs-platform\u002F06.built-in-modules-fs",{"title":4237,"path":4238,"stem":4239},"Вбудований модуль path","\u002Fweb-development\u002Fnodejs-platform\u002Fbuilt-in-modules-path","18.web-development\u002F05.nodejs-platform\u002F07.built-in-modules-path",{"title":4241,"path":4242,"stem":4243},"Вбудований модуль http","\u002Fweb-development\u002Fnodejs-platform\u002Fbuilt-in-modules-http","18.web-development\u002F05.nodejs-platform\u002F08.built-in-modules-http",{"title":4245,"path":4246,"stem":4247},"Streams — потоки даних у Node.js","\u002Fweb-development\u002Fnodejs-platform\u002Fstreams","18.web-development\u002F05.nodejs-platform\u002F09.streams",{"title":4249,"path":4250,"stem":4251},"Вбудований модуль util (Utilities)","\u002Fweb-development\u002Fnodejs-platform\u002Fbuilt-in-modules-util","18.web-development\u002F05.nodejs-platform\u002F10.built-in-modules-util",{"title":3141,"path":4253,"stem":4254},"\u002Fweb-development\u002Fnodejs-platform\u002Fenvironment-variables","18.web-development\u002F05.nodejs-platform\u002F11.environment-variables",{"title":4256,"path":4257,"stem":4258},"Інструменти налагодження та розробки","\u002Fweb-development\u002Fnodejs-platform\u002Fdebugging-tools","18.web-development\u002F05.nodejs-platform\u002F12.debugging-tools",{"title":4260,"path":4261,"stem":4262},"Продуктивність та Best Practices","\u002Fweb-development\u002Fnodejs-platform\u002Fperformance-best-practices","18.web-development\u002F05.nodejs-platform\u002F13.performance-best-practices",{"title":4264,"icon":4265,"path":4266,"stem":4267,"children":4268,"page":59},"Асинхронне програмування у Node.js","i-lucide-clock","\u002Fweb-development\u002Fasync-programming-nodejs","18.web-development\u002F06.async-programming-nodejs",[4269,4273,4277,4281,4285,4289,4293,4297,4301,4305,4309],{"title":4270,"path":4271,"stem":4272},"Синхронний vs асинхронний код","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fsync-vs-async","18.web-development\u002F06.async-programming-nodejs\u002F01.sync-vs-async",{"title":4274,"path":4275,"stem":4276},"Callbacks — перша парадигма асинхронності","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fcallbacks","18.web-development\u002F06.async-programming-nodejs\u002F02.callbacks",{"title":4278,"path":4279,"stem":4280},"Promises — стандарт асинхронності","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fpromises","18.web-development\u002F06.async-programming-nodejs\u002F03.promises",{"title":4282,"path":4283,"stem":4284},"Promise комбінатори","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fpromise-combinators","18.web-development\u002F06.async-programming-nodejs\u002F04.promise-combinators",{"title":4286,"path":4287,"stem":4288},"Async\u002FAwait — синтаксичний цукор над Promises","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fasync-await","18.web-development\u002F06.async-programming-nodejs\u002F05.async-await",{"title":4290,"path":4291,"stem":4292},"Паралельне vs послідовне виконання","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fparallel-vs-sequential","18.web-development\u002F06.async-programming-nodejs\u002F06.parallel-vs-sequential",{"title":4294,"path":4295,"stem":4296},"EventEmitter — подієва модель Node.js","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fevent-emitter","18.web-development\u002F06.async-programming-nodejs\u002F07.event-emitter",{"title":4298,"path":4299,"stem":4300},"Worker Threads — багатопотоковість у Node.js","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fworker-threads","18.web-development\u002F06.async-programming-nodejs\u002F08.worker-threads",{"title":4302,"path":4303,"stem":4304},"Child Processes — запуск зовнішніх процесів","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fchild-processes","18.web-development\u002F06.async-programming-nodejs\u002F09.child-processes",{"title":4306,"path":4307,"stem":4308},"Обробка помилок у асинхронному коді","\u002Fweb-development\u002Fasync-programming-nodejs\u002Ferror-handling","18.web-development\u002F06.async-programming-nodejs\u002F10.error-handling",{"title":4310,"path":4311,"stem":4312},"Порівняння Node.js фреймворків","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fnodejs-frameworks","18.web-development\u002F06.async-programming-nodejs\u002F11.nodejs-frameworks",{"title":4314,"icon":4315,"path":4316,"stem":4317,"children":4318,"page":59},"Тема 7. Фреймворк NestJS. Контролери та маршрутизація","i-lucide-route","\u002Fweb-development\u002Fnestjs-controllers-routing","18.web-development\u002F07.nestjs-controllers-routing",[4319,4323,4327,4331,4335,4339,4343,4347,4351,4355,4359,4363,4367,4371,4375,4379,4383,4387,4391,4395,4399,4403],{"title":4320,"path":4321,"stem":4322},"Філософія та архітектура NestJS","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fnestjs-philosophy","18.web-development\u002F07.nestjs-controllers-routing\u002F01.nestjs-philosophy",{"title":4324,"path":4325,"stem":4326},"Три стовпи архітектури: модулі, контролери, провайдери","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fthree-pillars","18.web-development\u002F07.nestjs-controllers-routing\u002F02.three-pillars",{"title":4328,"path":4329,"stem":4330},"Інверсія керування (IoC) та ін","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fioc-and-di","18.web-development\u002F07.nestjs-controllers-routing\u002F03.ioc-and-di",{"title":4332,"path":4333,"stem":4334},"Встановлення NestJS CLI та створення проєкту","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fnestjs-cli-setup","18.web-development\u002F07.nestjs-controllers-routing\u002F04.nestjs-cli-setup",{"title":4336,"path":4337,"stem":4338},"Структура проєкту NestJS та конвенції","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fproject-structure","18.web-development\u002F07.nestjs-controllers-routing\u002F05.project-structure",{"title":4340,"path":4341,"stem":4342},"Контролери: основи маршрутизації","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fcontrollers-basics","18.web-development\u002F07.nestjs-controllers-routing\u002F06.controllers-basics",{"title":4344,"path":4345,"stem":4346},"Декоратори маршрутизації HTTP-методів","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Froute-decorators","18.web-development\u002F07.nestjs-controllers-routing\u002F07.route-decorators",{"title":4348,"path":4349,"stem":4350},"Параметри маршруту та декоратор @Param","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Froute-parameters","18.web-development\u002F07.nestjs-controllers-routing\u002F08.route-parameters",{"title":4352,"path":4353,"stem":4354},"Query-параметри та декоратор @Query","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fquery-parameters","18.web-development\u002F07.nestjs-controllers-routing\u002F09.query-parameters",{"title":4356,"path":4357,"stem":4358},"Тіло запиту та декоратор @Body","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Frequest-body","18.web-development\u002F07.nestjs-controllers-routing\u002F10.request-body",{"title":4360,"path":4361,"stem":4362},"Робота з заголовками запиту та відповіді","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fheaders-decorators","18.web-development\u002F07.nestjs-controllers-routing\u002F11.headers-decorators",{"title":4364,"path":4365,"stem":4366},"Data Transfer Objects (DTO): визначення та призначення","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fdto-introduction","18.web-development\u002F07.nestjs-controllers-routing\u002F12.dto-introduction",{"title":4368,"path":4369,"stem":4370},"Об'єкти Request та Response","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Frequest-response-objects","18.web-development\u002F07.nestjs-controllers-routing\u002F13.request-response-objects",{"title":4372,"path":4373,"stem":4374},"HTTP-статус коди та декоратор @HttpCode","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fhttp-status-codes","18.web-development\u002F07.nestjs-controllers-routing\u002F14.http-status-codes",{"title":4376,"path":4377,"stem":4378},"Перенаправлення (Redirects) та декоратор @Redirect","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fredirects","18.web-development\u002F07.nestjs-controllers-routing\u002F15.redirects",{"title":4380,"path":4381,"stem":4382},"Асинхронні обробники та Observables","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fasync-handlers","18.web-development\u002F07.nestjs-controllers-routing\u002F16.async-handlers",{"title":4384,"path":4385,"stem":4386},"Маршрутизація за піддоменами та версіонування API","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fsub-domain-routing","18.web-development\u002F07.nestjs-controllers-routing\u002F17.sub-domain-routing",{"title":4388,"path":4389,"stem":4390},"Області видимості контролерів (Scopes)","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fcontroller-scopes","18.web-development\u002F07.nestjs-controllers-routing\u002F18.controller-scopes",{"title":4392,"path":4393,"stem":4394},"Основні команди NestJS CLI","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fnestjs-cli-commands","18.web-development\u002F07.nestjs-controllers-routing\u002F19.nestjs-cli-commands",{"title":4396,"path":4397,"stem":4398},"Практичний приклад: створення CRUD-контролера","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fcrud-example","18.web-development\u002F07.nestjs-controllers-routing\u002F20.crud-example",{"title":4400,"path":4401,"stem":4402},"Тестування контролерів","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Ftesting-controllers","18.web-development\u002F07.nestjs-controllers-routing\u002F21.testing-controllers",{"title":4404,"path":4405,"stem":4406},"Best Practices для контролерів та маршрутизації","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fbest-practices","18.web-development\u002F07.nestjs-controllers-routing\u002F22.best-practices",{"title":4408,"icon":4409,"path":4410,"stem":4411,"children":4412,"page":59},"Тема 8. Провайдери, сервіси та модульна система NestJS","i-lucide-package","\u002Fweb-development\u002Fnestjs-providers-modules","18.web-development\u002F08.nestjs-providers-modules",[4413,4417,4421,4425,4429,4433,4437,4441,4445,4449,4453,4457,4461,4465,4469],{"title":4414,"path":4415,"stem":4416},"Концепція провайдерів у NestJS","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fproviders-concept","18.web-development\u002F08.nestjs-providers-modules\u002F01.providers-concept",{"title":4418,"path":4419,"stem":4420},"Сервіси: інкапсуляція бізнес-логіки","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fservices-business-logic","18.web-development\u002F08.nestjs-providers-modules\u002F02.services-business-logic",{"title":4422,"path":4423,"stem":4424},"Практика ін","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fdependency-injection-practice","18.web-development\u002F08.nestjs-providers-modules\u002F03.dependency-injection-practice",{"title":4426,"path":4427,"stem":4428},"Custom Providers: useValue, useClass, useFactory, useExisting","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fcustom-providers","18.web-development\u002F08.nestjs-providers-modules\u002F04.custom-providers",{"title":4430,"path":4431,"stem":4432},"Injection Tokens: рядкові та символьні токени","\u002Fweb-development\u002Fnestjs-providers-modules\u002Finjection-tokens","18.web-development\u002F08.nestjs-providers-modules\u002F05.injection-tokens",{"title":4434,"path":4435,"stem":4436},"Опціональні провайдери та декоратор @Optional","\u002Fweb-development\u002Fnestjs-providers-modules\u002Foptional-providers","18.web-development\u002F08.nestjs-providers-modules\u002F07.optional-providers",{"title":4438,"path":4439,"stem":4440},"Структура модулів: imports, controllers, providers, exports","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fmodules-structure","18.web-development\u002F08.nestjs-providers-modules\u002F08.modules-structure",{"title":4442,"path":4443,"stem":4444},"Feature Modules: ізоляція функціональності","\u002Fweb-development\u002Fnestjs-providers-modules\u002Ffeature-modules","18.web-development\u002F08.nestjs-providers-modules\u002F09.feature-modules",{"title":4446,"path":4447,"stem":4448},"Shared Modules: перевикористання провайдерів","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fshared-modules","18.web-development\u002F08.nestjs-providers-modules\u002F10.shared-modules",{"title":4450,"path":4451,"stem":4452},"Global Modules та декоратор @Global","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fglobal-modules","18.web-development\u002F08.nestjs-providers-modules\u002F11.global-modules",{"title":4454,"path":4455,"stem":4456},"Dynamic Modules: конфігурація під час виконання","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fdynamic-modules","18.web-development\u002F08.nestjs-providers-modules\u002F12.dynamic-modules",{"title":4458,"path":4459,"stem":4460},"Циклічні залежності та forwardRef","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fcircular-dependencies","18.web-development\u002F08.nestjs-providers-modules\u002F13.circular-dependencies",{"title":4462,"path":4463,"stem":4464},"Lifecycle Hooks: хуки життєвого циклу","\u002Fweb-development\u002Fnestjs-providers-modules\u002Flifecycle-hooks","18.web-development\u002F08.nestjs-providers-modules\u002F14.lifecycle-hooks",{"title":4466,"path":4467,"stem":4468},"ModuleRef: динамічний доступ до провайдерів","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fmodule-reference","18.web-development\u002F08.nestjs-providers-modules\u002F15.module-reference",{"title":4470,"path":4471,"stem":4472},"Тестування сервісів та провайдерів","\u002Fweb-development\u002Fnestjs-providers-modules\u002Ftesting-services","18.web-development\u002F08.nestjs-providers-modules\u002F16.testing-services",{"title":4474,"icon":4475,"path":4476,"stem":4477,"children":4478,"page":59},"Тема 9. Валідація даних та конвеєр обробки запитів у NestJS","i-lucide-filter","\u002Fweb-development\u002Fnestjs-validation-pipeline","18.web-development\u002F09.nestjs-validation-pipeline",[4479,4483,4487,4491,4495,4499,4503,4507,4511,4515,4519,4523,4527,4531,4535,4539,4543,4547,4551],{"title":4480,"path":4481,"stem":4482},"Request Pipeline: конвеєр обробки запитів","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Frequest-pipeline","18.web-development\u002F09.nestjs-validation-pipeline\u002F01.request-pipeline",{"title":4484,"path":4485,"stem":4486},"Pipes: концепція трансформації та валідації","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fpipes-concept","18.web-development\u002F09.nestjs-validation-pipeline\u002F02.pipes-concept",{"title":4488,"path":4489,"stem":4490},"Вбудовані pipes: ParseIntPipe, ParseBoolPipe, ParseUUIDPipe","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fbuilt-in-pipes","18.web-development\u002F09.nestjs-validation-pipeline\u002F03.built-in-pipes",{"title":4492,"path":4493,"stem":4494},"ValidationPipe: автоматична валідація DTO","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fvalidation-pipe","18.web-development\u002F09.nestjs-validation-pipeline\u002F04.validation-pipe",{"title":4496,"path":4497,"stem":4498},"Декоратори class-validator для DTO","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fclass-validator-decorators","18.web-development\u002F09.nestjs-validation-pipeline\u002F05.class-validator-decorators",{"title":4500,"path":4501,"stem":4502},"Створення кастомних валідаторів","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fcustom-validators","18.web-development\u002F09.nestjs-validation-pipeline\u002F06.custom-validators",{"title":4504,"path":4505,"stem":4506},"Створення власних Pipes","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fcustom-pipes","18.web-development\u002F09.nestjs-validation-pipeline\u002F07.custom-pipes",{"title":4508,"path":4509,"stem":4510},"Основи Middleware","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fmiddleware-basics","18.web-development\u002F09.nestjs-validation-pipeline\u002F08.middleware-basics",{"title":4512,"path":4513,"stem":4514},"Практичні приклади Middleware","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fmiddleware-examples","18.web-development\u002F09.nestjs-validation-pipeline\u002F09.middleware-examples",{"title":4516,"path":4517,"stem":4518},"Guards: захисні перехоплювачі доступу","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fguards-concept","18.web-development\u002F09.nestjs-validation-pipeline\u002F10.guards-concept",{"title":4520,"path":4521,"stem":4522},"Створення кастомних Guards","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fcustom-guards","18.web-development\u002F09.nestjs-validation-pipeline\u002F11.custom-guards",{"title":4524,"path":4525,"stem":4526},"Interceptors: перехоплення та трансформація відповідей","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Finterceptors-concept","18.web-development\u002F09.nestjs-validation-pipeline\u002F12.interceptors-concept",{"title":4528,"path":4529,"stem":4530},"Практичні приклади Interceptors","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Finterceptor-examples","18.web-development\u002F09.nestjs-validation-pipeline\u002F13.interceptor-examples",{"title":4532,"path":4533,"stem":4534},"Exception Filters: обробка виключень","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fexception-filters","18.web-development\u002F09.nestjs-validation-pipeline\u002F14.exception-filters",{"title":4536,"path":4537,"stem":4538},"Custom Exception Filters: спеціалізовані фільтри","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fcustom-exception-filters","18.web-development\u002F09.nestjs-validation-pipeline\u002F15.custom-exception-filters",{"title":4540,"path":4541,"stem":4542},"Execution Context: контекст виконання","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fexecution-context","18.web-development\u002F09.nestjs-validation-pipeline\u002F16.execution-context",{"title":4544,"path":4545,"stem":4546},"Custom Decorators: власні декоратори","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fcustom-decorators","18.web-development\u002F09.nestjs-validation-pipeline\u002F17.custom-decorators",{"title":4548,"path":4549,"stem":4550},"Global Components: глобальні компоненти","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fglobal-components","18.web-development\u002F09.nestjs-validation-pipeline\u002F18.global-components",{"title":4552,"path":4553,"stem":4554},"Pipeline Best Practices: найкращі практики","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fpipeline-best-practices","18.web-development\u002F09.nestjs-validation-pipeline\u002F19.pipeline-best-practices",{"title":4556,"icon":2865,"path":4557,"stem":4558,"children":4559,"page":59},"Інтеграція реляційних баз даних засобами TypeORM","\u002Fweb-development\u002Ftypeorm-integration","18.web-development\u002F10.typeorm-integration",[4560,4564,4568,4572,4576,4580,4584],{"title":4561,"path":4562,"stem":4563},"Робота з базами даних у Node.js через нативні драйвери","\u002Fweb-development\u002Ftypeorm-integration\u002F01-nodejs-database-drivers","18.web-development\u002F10.typeorm-integration\u002F01-nodejs-database-drivers",{"title":4565,"path":4566,"stem":4567},"ORM та знайомство з TypeORM","\u002Fweb-development\u002Ftypeorm-integration\u002F02-orm-and-typeorm-intro","18.web-development\u002F10.typeorm-integration\u002F02-orm-and-typeorm-intro",{"title":4569,"path":4570,"stem":4571},"Налаштування TypeORM у NestJS проєкті","\u002Fweb-development\u002Ftypeorm-integration\u002F03-typeorm-setup-nestjs","18.web-development\u002F10.typeorm-integration\u002F03-typeorm-setup-nestjs",{"title":4573,"path":4574,"stem":4575},"Entity класи та декоратори TypeORM","\u002Fweb-development\u002Ftypeorm-integration\u002F04-entities-and-decorators","18.web-development\u002F10.typeorm-integration\u002F04-entities-and-decorators",{"title":4577,"path":4578,"stem":4579},"Repository Pattern та CRUD операції","\u002Fweb-development\u002Ftypeorm-integration\u002F05-repository-pattern-crud","18.web-development\u002F10.typeorm-integration\u002F05-repository-pattern-crud",{"title":4581,"path":4582,"stem":4583},"Пагінація та фільтрація даних","\u002Fweb-development\u002Ftypeorm-integration\u002F06-pagination-filtering","18.web-development\u002F10.typeorm-integration\u002F06-pagination-filtering",{"title":4585,"path":4586,"stem":4587},"QueryBuilder для складних запитів","\u002Fweb-development\u002Ftypeorm-integration\u002F07-query-builder","18.web-development\u002F10.typeorm-integration\u002F07-query-builder",{"title":4589,"icon":4590,"path":4591,"stem":4592,"children":4593,"page":59},"Зв'язки між сутностями, міграції та оптимізація запитів","i-lucide-git-branch","\u002Fweb-development\u002Fentity-relations-migrations","18.web-development\u002F11.entity-relations-migrations",[4594,4598,4602,4606,4610],{"title":4595,"path":4596,"stem":4597},"Зв'язки One-to-Many та Many-to-One","\u002Fweb-development\u002Fentity-relations-migrations\u002F01-one-to-many-many-to-one","18.web-development\u002F11.entity-relations-migrations\u002F01-one-to-many-many-to-one",{"title":4599,"path":4600,"stem":4601},"Зв'язки One-to-One та Many-to-Many","\u002Fweb-development\u002Fentity-relations-migrations\u002F02-one-to-one-many-to-many","18.web-development\u002F11.entity-relations-migrations\u002F02-one-to-one-many-to-many",{"title":4603,"path":4604,"stem":4605},"Керування міграціями бази даних","\u002Fweb-development\u002Fentity-relations-migrations\u002F03-migrations-management","18.web-development\u002F11.entity-relations-migrations\u002F03-migrations-management",{"title":4607,"path":4608,"stem":4609},"Транзакції у TypeORM","\u002Fweb-development\u002Fentity-relations-migrations\u002F04-transactions","18.web-development\u002F11.entity-relations-migrations\u002F04-transactions",{"title":4611,"path":4612,"stem":4613,"children":4614},"Індекси та оптимізація запитів","\u002Fweb-development\u002Fentity-relations-migrations\u002F05-indexes-optimization","18.web-development\u002F11.entity-relations-migrations\u002F05-indexes-optimization",[4615],{"title":4611,"path":4612,"stem":4613},{"title":4617,"icon":4618,"path":4619,"stem":4620,"children":4621,"page":59},"Механізми автентифікації у вебзастосунках","i-lucide-key","\u002Fweb-development\u002Fauthentication","18.web-development\u002F12.authentication",[4622,4626,4630,4634,4638,4642,4646,4650,4654],{"title":4623,"path":4624,"stem":4625},"Автентифікація vs Авторизація","\u002Fweb-development\u002Fauthentication\u002F01-authentication-vs-authorization","18.web-development\u002F12.authentication\u002F01-authentication-vs-authorization",{"title":4627,"path":4628,"stem":4629},"Стратегії автентифікації","\u002Fweb-development\u002Fauthentication\u002F02-authentication-strategies","18.web-development\u002F12.authentication\u002F02-authentication-strategies",{"title":4631,"path":4632,"stem":4633},"Автентифікація на основі сесій","\u002Fweb-development\u002Fauthentication\u002F03-session-based-authentication","18.web-development\u002F12.authentication\u002F03-session-based-authentication",{"title":4635,"path":4636,"stem":4637},"Структура JSON Web Token (JWT)","\u002Fweb-development\u002Fauthentication\u002F04-jwt-structure","18.web-development\u002F12.authentication\u002F04-jwt-structure",{"title":4639,"path":4640,"stem":4641},"Інтеграція JWT у NestJS","\u002Fweb-development\u002Fauthentication\u002F05-nestjs-jwt-integration","18.web-development\u002F12.authentication\u002F05-nestjs-jwt-integration",{"title":4643,"path":4644,"stem":4645},"Passport.js стратегії у NestJS","\u002Fweb-development\u002Fauthentication\u002F06-passport-strategies","18.web-development\u002F12.authentication\u002F06-passport-strategies",{"title":4647,"path":4648,"stem":4649},"Безпечне зберігання паролів: хешування та криптографічний захист","\u002Fweb-development\u002Fauthentication\u002F07-password-hashing","18.web-development\u002F12.authentication\u002F07-password-hashing",{"title":4651,"path":4652,"stem":4653},"Refresh Token та безпечне оновлення доступу","\u002Fweb-development\u002Fauthentication\u002F08-refresh-tokens","18.web-development\u002F12.authentication\u002F08-refresh-tokens",{"title":4655,"path":4656,"stem":4657},"OAuth 2.0 та OpenID Connect: делегована автентифікація","\u002Fweb-development\u002Fauthentication\u002F09-oauth2-openid","18.web-development\u002F12.authentication\u002F09-oauth2-openid",{"title":4659,"icon":4660,"path":4661,"stem":4662,"children":4663,"page":59},"Авторизація та безпека серверних застосунків","i-lucide-shield","\u002Fweb-development\u002Fauthorization-security","18.web-development\u002F13.authorization-security",[4664,4668,4672,4676,4680,4684,4688,4692,4696,4700],{"title":4665,"path":4666,"stem":4667},"Моделі авторизації","\u002Fweb-development\u002Fauthorization-security\u002F01-authorization-models","18.web-development\u002F13.authorization-security\u002F01-authorization-models",{"title":4669,"path":4670,"stem":4671},"Реалізація RBAC у NestJS","\u002Fweb-development\u002Fauthorization-security\u002F02-rbac-implementation","18.web-development\u002F13.authorization-security\u002F02-rbac-implementation",{"title":4673,"path":4674,"stem":4675},"Permission-Based Access Control","\u002Fweb-development\u002Fauthorization-security\u002F03-permission-based-access","18.web-development\u002F13.authorization-security\u002F03-permission-based-access",{"title":4677,"path":4678,"stem":4679},"ABAC та бібліотека CASL","\u002Fweb-development\u002Fauthorization-security\u002F04-abac-casl","18.web-development\u002F13.authorization-security\u002F04-abac-casl",{"title":4681,"path":4682,"stem":4683},"Кастомні декоратори та метадані","\u002Fweb-development\u002Fauthorization-security\u002F05-custom-decorators-metadata","18.web-development\u002F13.authorization-security\u002F05-custom-decorators-metadata",{"title":4685,"path":4686,"stem":4687},"Конфігурація CORS","\u002Fweb-development\u002Fauthorization-security\u002F06-cors-configuration","18.web-development\u002F13.authorization-security\u002F06-cors-configuration",{"title":4689,"path":4690,"stem":4691},"Захист через HTTP Security Headers (Helmet)","\u002Fweb-development\u002Fauthorization-security\u002F07-helmet-security-headers","18.web-development\u002F13.authorization-security\u002F07-helmet-security-headers",{"title":4693,"path":4694,"stem":4695},"Rate Limiting та Throttling","\u002Fweb-development\u002Fauthorization-security\u002F08-rate-limiting-throttling","18.web-development\u002F13.authorization-security\u002F08-rate-limiting-throttling",{"title":4697,"path":4698,"stem":4699},"Захист від поширених атак","\u002Fweb-development\u002Fauthorization-security\u002F09-common-attacks-protection","18.web-development\u002F13.authorization-security\u002F09-common-attacks-protection",{"title":4701,"path":4702,"stem":4703},"HTTPS у продакшені","\u002Fweb-development\u002Fauthorization-security\u002F10-https-production","18.web-development\u002F13.authorization-security\u002F10-https-production",{"title":4705,"icon":871,"path":4706,"stem":4707,"children":4708,"page":59},"Комунікація у реальному часі, нотифікації та фонові задачі","\u002Fweb-development\u002Frealtime-notifications-jobs","18.web-development\u002F14.realtime-notifications-jobs",[4709,4713,4717,4721,4725,4729,4732,4735,4739,4743],{"title":4710,"path":4711,"stem":4712},"Методи комунікації у реальному часі","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F01-realtime-communication-methods","18.web-development\u002F14.realtime-notifications-jobs\u002F01-realtime-communication-methods",{"title":4714,"path":4715,"stem":4716},"WebSocket Gateway у NestJS","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F02-websocket-gateway","18.web-development\u002F14.realtime-notifications-jobs\u002F02-websocket-gateway",{"title":4718,"path":4719,"stem":4720},"Lifecycle та Rooms у WebSocket","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F03-websocket-lifecycle-rooms","18.web-development\u002F14.realtime-notifications-jobs\u002F03-websocket-lifecycle-rooms",{"title":4722,"path":4723,"stem":4724},"Server-Sent Events (SSE)","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F04-server-sent-events","18.web-development\u002F14.realtime-notifications-jobs\u002F04-server-sent-events",{"title":4726,"path":4727,"stem":4728},"Архітектура системи нотифікацій","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F05-notification-system","18.web-development\u002F14.realtime-notifications-jobs\u002F05-notification-system",{"title":904,"path":4730,"stem":4731},"\u002Fweb-development\u002Frealtime-notifications-jobs\u002F06-email-notifications","18.web-development\u002F14.realtime-notifications-jobs\u002F06-email-notifications",{"title":900,"path":4733,"stem":4734},"\u002Fweb-development\u002Frealtime-notifications-jobs\u002F07-web-push-notifications","18.web-development\u002F14.realtime-notifications-jobs\u002F07-web-push-notifications",{"title":4736,"path":4737,"stem":4738},"Фонові задачі та черги","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F08-background-jobs-queues","18.web-development\u002F14.realtime-notifications-jobs\u002F08-background-jobs-queues",{"title":4740,"path":4741,"stem":4742},"Планувальники та Cron jobs","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F09-schedulers-cron","18.web-development\u002F14.realtime-notifications-jobs\u002F09-schedulers-cron",{"title":4744,"path":4745,"stem":4746},"Практичні сценарії застосування","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F10-practical-scenarios","18.web-development\u002F14.realtime-notifications-jobs\u002F10-practical-scenarios",{"title":4748,"icon":4749,"path":4750,"stem":4751,"children":4752,"page":59},"Тестування, документування та розгортання застосунків","i-lucide-rocket","\u002Fweb-development\u002Ftesting-documentation-deployment","18.web-development\u002F15.testing-documentation-deployment",[4753,4757,4761,4765,4769,4773,4777,4781,4785,4789],{"title":4754,"path":4755,"stem":4756},"Піраміда тестування та стратегія","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F01-testing-pyramid-strategy","18.web-development\u002F15.testing-documentation-deployment\u002F01-testing-pyramid-strategy",{"title":4758,"path":4759,"stem":4760},"Основи Jest у NestJS","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F02-jest-nestjs-basics","18.web-development\u002F15.testing-documentation-deployment\u002F02-jest-nestjs-basics",{"title":4762,"path":4763,"stem":4764},"Unit-тестування сервісів","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F03-unit-testing-services","18.web-development\u002F15.testing-documentation-deployment\u002F03-unit-testing-services",{"title":4766,"path":4767,"stem":4768},"E2E тестування та покриття коду","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F04-e2e-testing-coverage","18.web-development\u002F15.testing-documentation-deployment\u002F04-e2e-testing-coverage",{"title":4770,"path":4771,"stem":4772},"Swagger, OpenAPI, Scalar та Arazzo","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F05-swagger-openapi","18.web-development\u002F15.testing-documentation-deployment\u002F05-swagger-openapi",{"title":4774,"path":4775,"stem":4776},"Керування конфігурацією","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F06-configuration-management","18.web-development\u002F15.testing-documentation-deployment\u002F06-configuration-management",{"title":4778,"path":4779,"stem":4780},"Docker та контейнеризація","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F07-docker-containerization","18.web-development\u002F15.testing-documentation-deployment\u002F07-docker-containerization",{"title":4782,"path":4783,"stem":4784},"CI\u002FCD Pipelines","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F08-cicd-pipelines","18.web-development\u002F15.testing-documentation-deployment\u002F08-cicd-pipelines",{"title":4786,"path":4787,"stem":4788},"Логування та моніторинг","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F09-logging-monitoring","18.web-development\u002F15.testing-documentation-deployment\u002F09-logging-monitoring",{"title":4790,"path":4791,"stem":4792},"Серіалізація та компресія","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F10-serialization-compression","18.web-development\u002F15.testing-documentation-deployment\u002F10-serialization-compression",{"title":4794,"icon":4795,"path":4796,"stem":4797,"children":4798,"page":59},"AI Core: мислення AI","i-lucide-brain","\u002Fai-core","19.ai-core",[4799,4840,4889,4927],{"title":4800,"icon":4749,"path":4801,"stem":4802,"children":4803,"page":59},"Вхід у професію AI Native Developer","\u002Fai-core\u002Fai-native-developer","19.ai-core\u002F01.ai-native-developer",[4804,4808,4812,4816,4820,4824,4828,4832,4836],{"title":4805,"path":4806,"stem":4807},"Вступ до професії розробника цифрових продуктів","\u002Fai-core\u002Fai-native-developer\u002Fdigital-products","19.ai-core\u002F01.ai-native-developer\u002F01.digital-products",{"title":4809,"path":4810,"stem":4811},"Професія розробника програмного забезпечення","\u002Fai-core\u002Fai-native-developer\u002Fsoftware-developer","19.ai-core\u002F01.ai-native-developer\u002F02.software-developer",{"title":4813,"path":4814,"stem":4815},"Професія AI Native Developer","\u002Fai-core\u002Fai-native-developer\u002Fai-native-developer","19.ai-core\u002F01.ai-native-developer\u002F03.ai-native-developer",{"title":4817,"path":4818,"stem":4819},"Вплив AI на розробку програмного забезпечення","\u002Fai-core\u002Fai-native-developer\u002Fai-impact-on-development","19.ai-core\u002F01.ai-native-developer\u002F04.ai-impact-on-development",{"title":4821,"path":4822,"stem":4823},"Життєвий цикл цифрового продукту","\u002Fai-core\u002Fai-native-developer\u002Fproduct-lifecycle","19.ai-core\u002F01.ai-native-developer\u002F05.product-lifecycle",{"title":4825,"path":4826,"stem":4827},"Застосування AI на етапах створення цифрового продукту","\u002Fai-core\u002Fai-native-developer\u002Fai-in-product-creation","19.ai-core\u002F01.ai-native-developer\u002F06.ai-in-product-creation",{"title":4829,"path":4830,"stem":4831},"Розподіл завдань між людиною та AI","\u002Fai-core\u002Fai-native-developer\u002Fhuman-vs-ai-tasks","19.ai-core\u002F01.ai-native-developer\u002F07.human-vs-ai-tasks",{"title":4833,"path":4834,"stem":4835},"Компетенції AI Native Developer","\u002Fai-core\u002Fai-native-developer\u002Fcompetencies","19.ai-core\u002F01.ai-native-developer\u002F08.competencies",{"title":4837,"path":4838,"stem":4839},"Карта професійного розвитку AI Native Developer","\u002Fai-core\u002Fai-native-developer\u002Fcareer-roadmap","19.ai-core\u002F01.ai-native-developer\u002F09.career-roadmap",{"title":4841,"icon":255,"path":4842,"stem":4843,"children":4844,"page":59},"Штучний інтелект і машинне навчання","\u002Fai-core\u002Fai-and-machine-learning","19.ai-core\u002F02.ai-and-machine-learning",[4845,4849,4853,4857,4861,4865,4869,4873,4877,4881,4885],{"title":4846,"path":4847,"stem":4848},"Штучний інтелект","\u002Fai-core\u002Fai-and-machine-learning\u002Fwhat-is-ai","19.ai-core\u002F02.ai-and-machine-learning\u002F01.what-is-ai",{"title":4850,"path":4851,"stem":4852},"Відмінність AI від інших програмних систем","\u002Fai-core\u002Fai-and-machine-learning\u002Fai-vs-automation","19.ai-core\u002F02.ai-and-machine-learning\u002F02.ai-vs-automation",{"title":4854,"path":4855,"stem":4856},"Завдання штучного інтелекту","\u002Fai-core\u002Fai-and-machine-learning\u002Fai-tasks","19.ai-core\u002F02.ai-and-machine-learning\u002F03.ai-tasks",{"title":4858,"path":4859,"stem":4860},"Machine Learning","\u002Fai-core\u002Fai-and-machine-learning\u002Fmachine-learning","19.ai-core\u002F02.ai-and-machine-learning\u002F04.machine-learning",{"title":4862,"path":4863,"stem":4864},"Machine Learning Workflow","\u002Fai-core\u002Fai-and-machine-learning\u002Fml-workflow","19.ai-core\u002F02.ai-and-machine-learning\u002F05.ml-workflow",{"title":4866,"path":4867,"stem":4868},"Типи машинного навчання","\u002Fai-core\u002Fai-and-machine-learning\u002Fml-types","19.ai-core\u002F02.ai-and-machine-learning\u002F06.ml-types",{"title":4870,"path":4871,"stem":4872},"Generative AI","\u002Fai-core\u002Fai-and-machine-learning\u002Fgenerative-ai","19.ai-core\u002F02.ai-and-machine-learning\u002F07.generative-ai",{"title":4874,"path":4875,"stem":4876},"Типи контенту, створюваного AI","\u002Fai-core\u002Fai-and-machine-learning\u002Fai-content-types","19.ai-core\u002F02.ai-and-machine-learning\u002F08.ai-content-types",{"title":4878,"path":4879,"stem":4880},"Великі мовні моделі","\u002Fai-core\u002Fai-and-machine-learning\u002Flarge-language-models","19.ai-core\u002F02.ai-and-machine-learning\u002F09.large-language-models",{"title":4882,"path":4883,"stem":4884},"Можливості та обмеження Generative AI","\u002Fai-core\u002Fai-and-machine-learning\u002Fcapabilities-and-limitations","19.ai-core\u002F02.ai-and-machine-learning\u002F10.capabilities-and-limitations",{"title":4886,"path":4887,"stem":4888},"Сучасні AI-асистенти","\u002Fai-core\u002Fai-and-machine-learning\u002Fmodern-ai-assistants","19.ai-core\u002F02.ai-and-machine-learning\u002F11.modern-ai-assistants",{"title":4890,"icon":4891,"path":4892,"stem":4893,"children":4894,"page":59},"Постановка завдань для AI: принципи створення промптів","i-lucide-message-square-text","\u002Fai-core\u002Fprompt-engineering","19.ai-core\u002F03.prompt-engineering",[4895,4899,4903,4907,4911,4915,4919,4923],{"title":4896,"path":4897,"stem":4898},"Промпт як інструмент","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-as-tool","19.ai-core\u002F03.prompt-engineering\u002F01.prompt-as-tool",{"title":4900,"path":4901,"stem":4902},"Принципи створення промптів","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-principles","19.ai-core\u002F03.prompt-engineering\u002F02.prompt-principles",{"title":4904,"path":4905,"stem":4906},"Структура промпта","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-structure","19.ai-core\u002F03.prompt-engineering\u002F03.prompt-structure",{"title":4908,"path":4909,"stem":4910},"Види промптів за типом задачі","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-types","19.ai-core\u002F03.prompt-engineering\u002F04.prompt-types",{"title":4912,"path":4913,"stem":4914},"Прийоми посилення промпта","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-enhancement","19.ai-core\u002F03.prompt-engineering\u002F05.prompt-enhancement",{"title":4916,"path":4917,"stem":4918},"Розбір і покращення промпта","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-analysis","19.ai-core\u002F03.prompt-engineering\u002F06.prompt-analysis",{"title":4920,"path":4921,"stem":4922},"Типові помилки під час створення промптів","\u002Fai-core\u002Fprompt-engineering\u002Fcommon-mistakes","19.ai-core\u002F03.prompt-engineering\u002F07.common-mistakes",{"title":4924,"path":4925,"stem":4926},"Практикум: особиста бібліотека промптів","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-library","19.ai-core\u002F03.prompt-engineering\u002F08.prompt-library",{"title":4928,"icon":793,"path":4929,"stem":4930,"children":4931,"page":59},"Перевірка результатів, безпека та AI Native Workflow","\u002Fai-core\u002Fverification-security-workflow","19.ai-core\u002F04.verification-security-workflow",[4932,4936,4940,4944,4948,4952,4956,4960,4964],{"title":4933,"path":4934,"stem":4935},"Межі можливостей AI","\u002Fai-core\u002Fverification-security-workflow\u002Fai-limitations","19.ai-core\u002F04.verification-security-workflow\u002F01.ai-limitations",{"title":4937,"path":4938,"stem":4939},"Галюцинації AI","\u002Fai-core\u002Fverification-security-workflow\u002Fai-hallucinations","19.ai-core\u002F04.verification-security-workflow\u002F02.ai-hallucinations",{"title":4941,"path":4942,"stem":4943},"Критичне мислення під час роботи з AI","\u002Fai-core\u002Fverification-security-workflow\u002Fcritical-thinking","19.ai-core\u002F04.verification-security-workflow\u002F03.critical-thinking",{"title":4945,"path":4946,"stem":4947},"Перевірка результатів роботи AI","\u002Fai-core\u002Fverification-security-workflow\u002Fresult-verification","19.ai-core\u002F04.verification-security-workflow\u002F04.result-verification",{"title":4949,"path":4950,"stem":4951},"Захист даних під час роботи з AI","\u002Fai-core\u002Fverification-security-workflow\u002Fdata-protection","19.ai-core\u002F04.verification-security-workflow\u002F05.data-protection",{"title":4953,"path":4954,"stem":4955},"Авторське право та навчальна доброчесність","\u002Fai-core\u002Fverification-security-workflow\u002Fcopyright-integrity","19.ai-core\u002F04.verification-security-workflow\u002F06.copyright-integrity",{"title":4957,"path":4958,"stem":4959},"Відповідальне використання AI","\u002Fai-core\u002Fverification-security-workflow\u002Fresponsible-use","19.ai-core\u002F04.verification-security-workflow\u002F07.responsible-use",{"title":4961,"path":4962,"stem":4963},"AI Native Workflow","\u002Fai-core\u002Fverification-security-workflow\u002Fai-native-workflow","19.ai-core\u002F04.verification-security-workflow\u002F08.ai-native-workflow",{"title":4965,"path":4966,"stem":4967},"Застосування AI Native Workflow під час створення цифрового продукту","\u002Fai-core\u002Fverification-security-workflow\u002Fworkflow-in-practice","19.ai-core\u002F04.verification-security-workflow\u002F09.workflow-in-practice",{"title":4969,"icon":4970,"path":4971,"stem":4972,"children":4973,"page":59},"AI Developer: Vibe Coding Sprint","i-lucide-code-xml","\u002Fai-developer","20.ai-developer",[4974,5000,5022,5043],{"title":4975,"icon":4976,"path":4977,"stem":4978,"children":4979,"page":59},"Проєктування і чорнова версія","i-lucide-pencil-ruler","\u002Fai-developer\u002Fdraft-creation","20.ai-developer\u002F01.draft-creation",[4980,4984,4988,4992,4996],{"title":4981,"path":4982,"stem":4983},"Парадигма Vibe Coding Workflow","\u002Fai-developer\u002Fdraft-creation\u002Fvibe-coding-workflow","20.ai-developer\u002F01.draft-creation\u002F01.vibe-coding-workflow",{"title":4985,"path":4986,"stem":4987},"AI-середовище швидкої розробки","\u002Fai-developer\u002Fdraft-creation\u002Fai-ide-environment","20.ai-developer\u002F01.draft-creation\u002F02.ai-ide-environment",{"title":4989,"path":4990,"stem":4991},"Користувацьке завдання та межі першої версії","\u002Fai-developer\u002Fdraft-creation\u002Fproduct-scope-and-mvp","20.ai-developer\u002F01.draft-creation\u002F03.product-scope-and-mvp",{"title":4993,"path":4994,"stem":4995},"Архітектура інтерфейсу та стани застосунку","\u002Fai-developer\u002Fdraft-creation\u002Fapplication-architecture-and-states","20.ai-developer\u002F01.draft-creation\u002F04.application-architecture-and-states",{"title":4997,"path":4998,"stem":4999},"Генерація та фіксація чорнової версії","\u002Fai-developer\u002Fdraft-creation\u002Fgenerating-draft-version","20.ai-developer\u002F01.draft-creation\u002F05.generating-draft-version",{"title":5001,"icon":5002,"path":5003,"stem":5004,"children":5005,"page":59},"Перша робоча версія","i-lucide-play-circle","\u002Fai-developer\u002Ffirst-working-version","20.ai-developer\u002F02.first-working-version",[5006,5010,5014,5018],{"title":5007,"path":5008,"stem":5009},"Уточнення контексту проєкту для AI","\u002Fai-developer\u002Ffirst-working-version\u002Frefining-project-context","20.ai-developer\u002F02.first-working-version\u002F01.refining-project-context",{"title":5011,"path":5012,"stem":5013},"Стратегія завдань для AI-розробки","\u002Fai-developer\u002Ffirst-working-version\u002Fai-prompting-strategy","20.ai-developer\u002F02.first-working-version\u002F02.ai-prompting-strategy",{"title":5015,"path":5016,"stem":5017},"Доопрацювання до першої робочої версії","\u002Fai-developer\u002Ffirst-working-version\u002Frefining-to-working-version","20.ai-developer\u002F02.first-working-version\u002F03.refining-to-working-version",{"title":5019,"path":5020,"stem":5021},"Перевірка першої робочої версії","\u002Fai-developer\u002Ffirst-working-version\u002Ftesting-first-working-version","20.ai-developer\u002F02.first-working-version\u002F04.testing-first-working-version",{"title":5023,"icon":3072,"path":5024,"stem":5025,"children":5026,"page":59},"Ітерації, дебагінг та відновлення","\u002Fai-developer\u002Fiteration-debugging-recovery","20.ai-developer\u002F03.iteration-debugging-recovery",[5027,5031,5035,5039],{"title":5028,"path":5029,"stem":5030},"Управління точковими змінами продукту","\u002Fai-developer\u002Fiteration-debugging-recovery\u002Fchange-management","20.ai-developer\u002F03.iteration-debugging-recovery\u002F01.change-management",{"title":5032,"path":5033,"stem":5034},"Надійність інтерфейсу та обробка помилок","\u002Fai-developer\u002Fiteration-debugging-recovery\u002Fscenario-reliability-and-errors","20.ai-developer\u002F03.iteration-debugging-recovery\u002F02.scenario-reliability-and-errors",{"title":5036,"path":5037,"stem":5038},"Керування контекстом і збереження версій","\u002Fai-developer\u002Fiteration-debugging-recovery\u002Fproject-context-and-versions","20.ai-developer\u002F03.iteration-debugging-recovery\u002F03.project-context-and-versions",{"title":5040,"path":5041,"stem":5042},"Збої AI-розробки, ліміти та аварійне відновлення","\u002Fai-developer\u002Fiteration-debugging-recovery\u002Fai-breakdowns-and-recovery","20.ai-developer\u002F03.iteration-debugging-recovery\u002F04.ai-breakdowns-and-recovery",{"title":5044,"icon":5045,"path":5046,"stem":5047,"children":5048,"page":59},"Перевірка та завершення продукту","i-lucide-check-check","\u002Fai-developer\u002Fverification-and-completion","20.ai-developer\u002F04.verification-and-completion",[5049,5053,5057],{"title":5050,"path":5051,"stem":5052},"Комплексний аудит та підсумкове тестування","\u002Fai-developer\u002Fverification-and-completion\u002Ffinal-product-testing","20.ai-developer\u002F04.verification-and-completion\u002F01.final-product-testing",{"title":5054,"path":5055,"stem":5056},"Підготовка підсумкової версії коду","\u002Fai-developer\u002Fverification-and-completion\u002Fpreparing-release-version","20.ai-developer\u002F04.verification-and-completion\u002F02.preparing-release-version",{"title":5058,"path":5059,"stem":5060},"Демонстрація, публікація та критерії оцінювання","\u002Fai-developer\u002Fverification-and-completion\u002Fproduct-showcase-and-publishing","20.ai-developer\u002F04.verification-and-completion\u002F03.product-showcase-and-publishing",{"title":5062,"path":5063,"stem":5064,"children":5065,"page":59},"Tailwind","\u002Ftailwind","21.tailwind",[5066,5070,5074,5078,5082,5086,5090,5094,5098,5102,5106,5110],{"title":5067,"path":5068,"stem":5069},"Що таке Tailwind CSS і навіщо він потрібен","\u002Ftailwind\u002Ftailwind-intro-philosophy","21.tailwind\u002F01.tailwind-intro-philosophy",{"title":5071,"path":5072,"stem":5073},"Встановлення та налаштування Tailwind CSS v4","\u002Ftailwind\u002Ftailwind-installation-setup","21.tailwind\u002F02.tailwind-installation-setup",{"title":5075,"path":5076,"stem":5077},"Utility-класи: основи та система Tailwind","\u002Ftailwind\u002Ftailwind-utility-classes-core","21.tailwind\u002F03.tailwind-utility-classes-core",{"title":5079,"path":5080,"stem":5081},"Layout: Flexbox та Grid через Tailwind","\u002Ftailwind\u002Ftailwind-flexbox-grid","21.tailwind\u002F04.tailwind-flexbox-grid",{"title":5083,"path":5084,"stem":5085},"Кастомізація теми через @theme у Tailwind v4","\u002Ftailwind\u002Ftailwind-theme-customization","21.tailwind\u002F05.tailwind-theme-customization",{"title":5087,"path":5088,"stem":5089},"Варіанти: hover, focus, responsive, dark mode та нові v4","\u002Ftailwind\u002Ftailwind-variants-states","21.tailwind\u002F06.tailwind-variants-states",{"title":5091,"path":5092,"stem":5093},"Типографіка та система кольорів у Tailwind v4","\u002Ftailwind\u002Ftailwind-typography-colors","21.tailwind\u002F07.tailwind-typography-colors",{"title":5095,"path":5096,"stem":5097},"Компоненти та повторюваність: @apply, @utility та патерни","\u002Ftailwind\u002Ftailwind-components-patterns","21.tailwind\u002F08.tailwind-components-patterns",{"title":5099,"path":5100,"stem":5101},"Темна тема та система дизайн-токенів у Tailwind v4","\u002Ftailwind\u002Ftailwind-dark-mode-theming","21.tailwind\u002F09.tailwind-dark-mode-theming",{"title":5103,"path":5104,"stem":5105},"Довільні значення та контейнерні запити у Tailwind v4","\u002Ftailwind\u002Ftailwind-arbitrary-container-queries","21.tailwind\u002F10.tailwind-arbitrary-container-queries",{"title":5107,"path":5108,"stem":5109},"Анімації, трансформації та 3D у Tailwind v4","\u002Ftailwind\u002Ftailwind-animations-transforms","21.tailwind\u002F11.tailwind-animations-transforms",{"title":5111,"path":5112,"stem":5113},"Tailwind CLI, PostCSS та інтеграція з фреймворками","\u002Ftailwind\u002Ftailwind-cli-tooling","21.tailwind\u002F12.tailwind-cli-tooling",{"title":5115,"path":5116,"stem":5117,"children":5118,"page":59},"React Typescript","\u002Freact-typescript","22.react-typescript",[5119,5144,5148,5152,5156,5160,5164,5168,5172],{"title":5120,"path":5121,"stem":5122,"children":5123,"page":59},"From Html To Project","\u002Freact-typescript\u002Ffrom-html-to-project","22.react-typescript\u002F01.from-html-to-project",[5124,5128,5132,5136,5140],{"title":5125,"path":5126,"stem":5127},"Від одного HTML-файлу до повноцінного проєкту","\u002Freact-typescript\u002Ffrom-html-to-project\u002Fevolution","22.react-typescript\u002F01.from-html-to-project\u002F01.evolution",{"title":5129,"path":5130,"stem":5131},"Що таке React","\u002Freact-typescript\u002Ffrom-html-to-project\u002Fwhat-is-react","22.react-typescript\u002F01.from-html-to-project\u002F02.what-is-react",{"title":5133,"path":5134,"stem":5135},"JSX та TSX — синтаксичний цукор, а не магія","\u002Freact-typescript\u002Ffrom-html-to-project\u002Fjsx-tsx-syntax","22.react-typescript\u002F01.from-html-to-project\u002F03.jsx-tsx-syntax",{"title":5137,"path":5138,"stem":5139},"Компоненти — будівельні блоки інтерфейсу","\u002Freact-typescript\u002Ffrom-html-to-project\u002Fcomponents","22.react-typescript\u002F01.from-html-to-project\u002F04.components",{"title":5141,"path":5142,"stem":5143},"JSX — розмітка всередині TypeScript","\u002Freact-typescript\u002Ffrom-html-to-project\u002Fjsx-expressions","22.react-typescript\u002F01.from-html-to-project\u002F05.jsx-expressions",{"title":5145,"path":5146,"stem":5147},"Хук useReducer: структуроване управління складним станом","\u002Freact-typescript\u002Fuse-reducer","22.react-typescript\u002F23.use-reducer",{"title":5149,"path":5150,"stem":5151},"Context API: передавання даних без «пропс-дрілінгу»","\u002Freact-typescript\u002Fcontext-api","22.react-typescript\u002F24.context-api",{"title":5153,"path":5154,"stem":5155},"Синхронізація з ефектами: хук useEffect та функції очищення","\u002Freact-typescript\u002Fuse-effect","22.react-typescript\u002F27.use-effect",{"title":5157,"path":5158,"stem":5159},"Можливо, вам не потрібен ефект: антипатерни та альтернативи","\u002Freact-typescript\u002Fyou-might-not-need-effect","22.react-typescript\u002F28.you-might-not-need-effect",{"title":5161,"path":5162,"stem":5163},"Життєвий цикл реактивних ефектів: мислення процесами синхронізації","\u002Freact-typescript\u002Flifecycle-of-reactive-effects","22.react-typescript\u002F29.lifecycle-of-reactive-effects",{"title":5165,"path":5166,"stem":5167},"Розділення подій та ефектів: реактивна проти нереактивної логіки","\u002Freact-typescript\u002Fseparating-events-from-effects","22.react-typescript\u002F30.separating-events-from-effects",{"title":5169,"path":5170,"stem":5171},"Видалення зайвих залежностей ефектів та оптимізація синхронізації","\u002Freact-typescript\u002Fremoving-effect-dependencies","22.react-typescript\u002F31.removing-effect-dependencies",{"title":5173,"path":5174,"stem":5175},"Кастомні хуки: повторне використання та композиція реактивної логіки","\u002Freact-typescript\u002Fcustom-hooks","22.react-typescript\u002F32.custom-hooks",{"title":5177,"path":5178,"stem":5179},"Тестування компонентів діаграм та пісочниць","\u002Ftest-components","98.test-components",{"id":5181,"title":3976,"body":5182,"description":17531,"extension":17532,"links":17533,"meta":17534,"navigation":5277,"path":3977,"seo":17535,"stem":3978,"__hash__":17536},"docs\u002F16.ai-python\u002F16.batching-normalization-deep-networks\u002F06.learning-rate-scheduling.md",{"type":5183,"value":5184,"toc":17493},"minimark",[5185,5190,5205,5208,5225,5232,5543,5548,5551,5617,5624,5634,5640,5711,5714,5718,5721,5725,5728,5731,5734,5759,5775,5779,5790,7210,7254,7258,7265,7317,7319,7323,7330,7334,7348,7351,7353,7376,7384,7453,7964,7969,7980,7985,7996,8002,8004,8008,8013,8016,8023,8457,8461,8469,8474,8476,8480,8491,8494,8501,8920,8924,8934,8938,8949,8954,8956,8960,8976,8979,8981,8998,9004,9517,9521,9536,9540,9547,9552,9581,9583,9587,9598,9612,10456,10460,10474,10478,10490,10495,10497,10501,10511,10515,10524,10537,10739,10744,10747,10753,11743,11748,11770,11845,11847,11851,11860,11866,11871,11874,11876,11890,11896,12464,12469,12483,12487,12498,12503,12505,12509,12518,12532,12535,13087,13092,13112,13116,13130,13134,13150,13155,13157,13161,13164,13192,13196,13250,13254,15393,15397,16858,16862,16976,16978,16982,16985,16989,17143,17147,17150,17340,17344,17347,17373,17375,17379,17446,17489],[5186,5187,5189],"h2",{"id":5188},"дилема-learning-rate-надто-швидко-чи-надто-повільно","Дилема learning rate — надто швидко чи надто повільно?",[5191,5192,5193,5194,5198,5199,5204],"p",{},"У попередній статті ми опанували проєктування глибоких мереж через Skip Connections та ResNet архітектуру. Ми побудували 56-шарову мережу, що досягла 92% accuracy на CIFAR-10 — вражаючий результат! Але під час навчання ми використовували фіксований ",[5195,5196,5197],"strong",{},"learning rate"," ",[5200,5201],"math-formula",{"tex":5202,":inline":5203},"\\eta = 0.1","true"," протягом перших 60 епох, потім різко зменшували його до 0.01 на епосі 60 та до 0.001 на епосі 80.",[5191,5206,5207],{},"Це рішення працювало, але виникають природні запитання:",[5209,5210,5211,5217,5221],"card-group",{},[5212,5213,5216],"card",{"icon":5214,"title":5215},"i-lucide-help-circle","❓ Чому саме ці епохи?","Чому ми зменшуємо LR саме на епохах 60 та 80? Що, якщо оптимальні точки — 55 та 75? Або 70 та 90? Чи існує спосіб визначити це автоматично?",[5212,5218,5220],{"icon":2990,"title":5219},"❓ Чому саме фактор 0.1?","Чому ми множимо LR на 0.1 (зменшуємо у 10 разів)? Що, якщо краще було б 0.5 (удвічі) або 0.2 (у 5 разів)? Звідки беруться ці \"магічні числа\"?",[5212,5222,5224],{"icon":1348,"title":5223},"❓ Чому різкі стрибки?","Чому ми різко змінюємо LR з 0.1 до 0.01 за одну епоху? Чи не краще було б плавне зменшення? Чи не втрачаємо ми швидкість конвергенції через занадто консервативний підхід?",[5191,5226,5227,5228,5231],{},"Більше того, розглянемо фундаментальну проблему ",[5195,5229,5230],{},"фіксованого learning rate",". Уявіть процес оптимізації як спуск з гори до долини (мінімуму втрат):",[5233,5234,5236],"plant-uml",{"alt":5235},"Проблема фіксованого learning rate",[5237,5238,5243],"pre",{"className":5239,"code":5240,"language":5241,"meta":5242,"style":5242},"language-plantuml shiki shiki-themes light-plus dark-plus dark-plus","@startuml\nskinparam style plain\nskinparam backgroundColor #FFFFFF\nskinparam defaultFontName \"Arial\"\n\n!define START_COLOR #FEE2E2\n!define GOOD_COLOR #DCFCE7\n!define BAD_COLOR #FEF3C7\n\npackage \"Ландшафт втрат (Loss Landscape)\" {\n  \n  rectangle \"Початок навчання\\n(епохи 1-20)\" as start #START_COLOR {\n    note right\n      🏔️ Далеко від мінімуму\n      📏 Великі градієнти\n      ⚡ Потрібен ВЕЛИКИЙ LR (0.1)\n      щоб швидко рухатись\n    end note\n  }\n  \n  rectangle \"Середина навчання\\n(епохи 20-60)\" as middle #GOOD_COLOR {\n    note right\n      ⛰️ Наближаємось до долини\n      📏 Градієнти зменшуються\n      ⚖️ LR 0.1 все ще OK,\n      але може стрибати\n    end note\n  }\n  \n  rectangle \"Кінець навчання\\n(епохи 60+)\" as end #BAD_COLOR {\n    note right\n      🎯 Близько до мінімуму\n      📏 Малі градієнти\n      ❌ LR 0.1 ЗАНАДТО ВЕЛИКИЙ\n      \n      Проблема: модель перестрибує\n      через оптимум туди-сюди,\n      не може \"влучити\"\n    end note\n  }\n}\n\nstart -down-> middle : LR = 0.1\nmiddle -down-> end : LR = 0.1 (занадто великий!)\n\nnote bottom of end\n  💡 Рішення: зменшити LR до 0.01 або 0.001\n  щоб зробити точніші кроки біля мінімуму\nend note\n\n@enduml\n","plantuml","",[5244,5245,5246,5254,5260,5266,5272,5279,5285,5291,5297,5302,5308,5314,5320,5326,5332,5338,5344,5350,5356,5362,5367,5373,5378,5384,5390,5396,5402,5407,5412,5417,5423,5428,5434,5440,5446,5452,5458,5464,5470,5475,5480,5486,5491,5497,5503,5508,5514,5520,5526,5532,5537],"code",{"__ignoreMap":5242},[5247,5248,5251],"span",{"class":5249,"line":5250},"line",1,[5247,5252,5253],{},"@startuml\n",[5247,5255,5257],{"class":5249,"line":5256},2,[5247,5258,5259],{},"skinparam style plain\n",[5247,5261,5263],{"class":5249,"line":5262},3,[5247,5264,5265],{},"skinparam backgroundColor #FFFFFF\n",[5247,5267,5269],{"class":5249,"line":5268},4,[5247,5270,5271],{},"skinparam defaultFontName \"Arial\"\n",[5247,5273,5275],{"class":5249,"line":5274},5,[5247,5276,5278],{"emptyLinePlaceholder":5277},true,"\n",[5247,5280,5282],{"class":5249,"line":5281},6,[5247,5283,5284],{},"!define START_COLOR #FEE2E2\n",[5247,5286,5288],{"class":5249,"line":5287},7,[5247,5289,5290],{},"!define GOOD_COLOR #DCFCE7\n",[5247,5292,5294],{"class":5249,"line":5293},8,[5247,5295,5296],{},"!define BAD_COLOR #FEF3C7\n",[5247,5298,5300],{"class":5249,"line":5299},9,[5247,5301,5278],{"emptyLinePlaceholder":5277},[5247,5303,5305],{"class":5249,"line":5304},10,[5247,5306,5307],{},"package \"Ландшафт втрат (Loss Landscape)\" {\n",[5247,5309,5311],{"class":5249,"line":5310},11,[5247,5312,5313],{},"  \n",[5247,5315,5317],{"class":5249,"line":5316},12,[5247,5318,5319],{},"  rectangle \"Початок навчання\\n(епохи 1-20)\" as start #START_COLOR {\n",[5247,5321,5323],{"class":5249,"line":5322},13,[5247,5324,5325],{},"    note right\n",[5247,5327,5329],{"class":5249,"line":5328},14,[5247,5330,5331],{},"      🏔️ Далеко від мінімуму\n",[5247,5333,5335],{"class":5249,"line":5334},15,[5247,5336,5337],{},"      📏 Великі градієнти\n",[5247,5339,5341],{"class":5249,"line":5340},16,[5247,5342,5343],{},"      ⚡ Потрібен ВЕЛИКИЙ LR (0.1)\n",[5247,5345,5347],{"class":5249,"line":5346},17,[5247,5348,5349],{},"      щоб швидко рухатись\n",[5247,5351,5353],{"class":5249,"line":5352},18,[5247,5354,5355],{},"    end note\n",[5247,5357,5359],{"class":5249,"line":5358},19,[5247,5360,5361],{},"  }\n",[5247,5363,5365],{"class":5249,"line":5364},20,[5247,5366,5313],{},[5247,5368,5370],{"class":5249,"line":5369},21,[5247,5371,5372],{},"  rectangle \"Середина навчання\\n(епохи 20-60)\" as middle #GOOD_COLOR {\n",[5247,5374,5376],{"class":5249,"line":5375},22,[5247,5377,5325],{},[5247,5379,5381],{"class":5249,"line":5380},23,[5247,5382,5383],{},"      ⛰️ Наближаємось до долини\n",[5247,5385,5387],{"class":5249,"line":5386},24,[5247,5388,5389],{},"      📏 Градієнти зменшуються\n",[5247,5391,5393],{"class":5249,"line":5392},25,[5247,5394,5395],{},"      ⚖️ LR 0.1 все ще OK,\n",[5247,5397,5399],{"class":5249,"line":5398},26,[5247,5400,5401],{},"      але може стрибати\n",[5247,5403,5405],{"class":5249,"line":5404},27,[5247,5406,5355],{},[5247,5408,5410],{"class":5249,"line":5409},28,[5247,5411,5361],{},[5247,5413,5415],{"class":5249,"line":5414},29,[5247,5416,5313],{},[5247,5418,5420],{"class":5249,"line":5419},30,[5247,5421,5422],{},"  rectangle \"Кінець навчання\\n(епохи 60+)\" as end #BAD_COLOR {\n",[5247,5424,5426],{"class":5249,"line":5425},31,[5247,5427,5325],{},[5247,5429,5431],{"class":5249,"line":5430},32,[5247,5432,5433],{},"      🎯 Близько до мінімуму\n",[5247,5435,5437],{"class":5249,"line":5436},33,[5247,5438,5439],{},"      📏 Малі градієнти\n",[5247,5441,5443],{"class":5249,"line":5442},34,[5247,5444,5445],{},"      ❌ LR 0.1 ЗАНАДТО ВЕЛИКИЙ\n",[5247,5447,5449],{"class":5249,"line":5448},35,[5247,5450,5451],{},"      \n",[5247,5453,5455],{"class":5249,"line":5454},36,[5247,5456,5457],{},"      Проблема: модель перестрибує\n",[5247,5459,5461],{"class":5249,"line":5460},37,[5247,5462,5463],{},"      через оптимум туди-сюди,\n",[5247,5465,5467],{"class":5249,"line":5466},38,[5247,5468,5469],{},"      не може \"влучити\"\n",[5247,5471,5473],{"class":5249,"line":5472},39,[5247,5474,5355],{},[5247,5476,5478],{"class":5249,"line":5477},40,[5247,5479,5361],{},[5247,5481,5483],{"class":5249,"line":5482},41,[5247,5484,5485],{},"}\n",[5247,5487,5489],{"class":5249,"line":5488},42,[5247,5490,5278],{"emptyLinePlaceholder":5277},[5247,5492,5494],{"class":5249,"line":5493},43,[5247,5495,5496],{},"start -down-> middle : LR = 0.1\n",[5247,5498,5500],{"class":5249,"line":5499},44,[5247,5501,5502],{},"middle -down-> end : LR = 0.1 (занадто великий!)\n",[5247,5504,5506],{"class":5249,"line":5505},45,[5247,5507,5278],{"emptyLinePlaceholder":5277},[5247,5509,5511],{"class":5249,"line":5510},46,[5247,5512,5513],{},"note bottom of end\n",[5247,5515,5517],{"class":5249,"line":5516},47,[5247,5518,5519],{},"  💡 Рішення: зменшити LR до 0.01 або 0.001\n",[5247,5521,5523],{"class":5249,"line":5522},48,[5247,5524,5525],{},"  щоб зробити точніші кроки біля мінімуму\n",[5247,5527,5529],{"class":5249,"line":5528},49,[5247,5530,5531],{},"end note\n",[5247,5533,5535],{"class":5249,"line":5534},50,[5247,5536,5278],{"emptyLinePlaceholder":5277},[5247,5538,5540],{"class":5249,"line":5539},51,[5247,5541,5542],{},"@enduml\n",[5544,5545,5547],"h3",{"id":5546},"метафора-водій-на-гірській-дорозі","Метафора — водій на гірській дорозі",[5191,5549,5550],{},"Уявіть, що ви водій автомобіля, який спускається зі стрімкої гори до готелю в долині:",[5209,5552,5553,5575,5594],{},[5212,5554,5557,5563,5569],{"icon":5555,"title":5556},"i-lucide-mountain","🏔️ Початок шляху (епохи 1-20)",[5191,5558,5559,5562],{},[5195,5560,5561],{},"Ситуація:"," Ви на вершині, дорога широка, прямий спуск.",[5191,5564,5565,5568],{},[5195,5566,5567],{},"Стратегія:"," Їдете швидко (80 км\u002Fгод). Чим швидше, тим краще — потрібно швидко покрити велику відстань.",[5191,5570,5571,5574],{},[5195,5572,5573],{},"Аналогія:"," Великий LR (0.1) — робимо великі кроки, бо далеко від мінімуму.",[5212,5576,5579,5584,5589],{"icon":5577,"title":5578},"i-lucide-map","⛰️ Середина шляху (епохи 20-60)",[5191,5580,5581,5583],{},[5195,5582,5561],{}," Дорога звужується, з'являються повороти.",[5191,5585,5586,5588],{},[5195,5587,5567],{}," Зменшуєте швидкість до 50 км\u002Fгод. Все ще швидко, але вже обережніше.",[5191,5590,5591,5593],{},[5195,5592,5573],{}," LR 0.1 все ще працює, але іноді \"проскакуємо\" повороти (локальні мінімуми).",[5212,5595,5598,5603,5612],{"icon":5596,"title":5597},"i-lucide-flag","🎯 Парковка біля готелю (епохи 60+)",[5191,5599,5600,5602],{},[5195,5601,5561],{}," Ви в долині, потрібно точно припаркуватися.",[5191,5604,5605,5607,5608,5611],{},[5195,5606,5567],{}," Якщо продовжите їхати 80 км\u002Fгод, ",[5195,5609,5610],{},"проїдете повз готель",", розвернетесь, знову проїдете, знову розвернетесь — нескінченне коливання! Потрібно зменшити до 5 км\u002Fгод для точного паркування.",[5191,5613,5614,5616],{},[5195,5615,5573],{}," Великий LR \"перестрибує\" через мінімум втрат. Потрібно зменшити LR для \"fine-tuning\".",[5191,5618,5619,5620,5623],{},"Саме тому фіксований learning rate ",[5195,5621,5622],{},"неефективний",":",[5625,5626,5627,5631],"ul",{},[5628,5629,5630],"li",{},"Початок навчання: можна було б їхати швидше → втрачаємо час",[5628,5632,5633],{},"Кінець навчання: їдемо занадто швидко → не можемо зупинитись у мінімумі",[5191,5635,5636,5639],{},[5195,5637,5638],{},"Learning Rate Scheduling"," — це систематичний підхід до зміни LR протягом навчання, що вирішує цю проблему.",[5209,5641,5642,5666],{},[5212,5643,5646],{"icon":5644,"title":5645},"i-lucide-target","🎯 Мета статті",[5625,5647,5648,5651,5654,5657,5660,5663],{},[5628,5649,5650],{},"Зрозуміти проблему фіксованого learning rate через візуалізацію ландшафту втрат",[5628,5652,5653],{},"Опанувати основні типи LR schedulers: StepLR, ExponentialLR, CosineAnnealingLR, ReduceLROnPlateau",[5628,5655,5656],{},"Дослідити advanced техніки: Warm-up, Warm Restarts (SGDR), OneCycleLR",[5628,5658,5659],{},"Навчитися обирати та налаштовувати scheduler для різних сценаріїв",[5628,5661,5662],{},"Провести експеримент на CIFAR-10: порівняти 5 різних стратегій scheduling",[5628,5664,5665],{},"Отримати практичні рекомендації для реальних проєктів",[5212,5667,5669],{"icon":4618,"title":5668},"🔑 Ключові терміни",[5625,5670,5671,5681,5687,5693,5699,5705],{},[5628,5672,5673,5676,5677,5680],{},[5195,5674,5675],{},"Learning Rate (LR):"," швидкість навчання ",[5200,5678],{"tex":5679,":inline":5203},"\\eta",", що контролює розмір кроку оптимізації",[5628,5682,5683,5686],{},[5195,5684,5685],{},"Scheduler:"," механізм автоматичної зміни LR протягом навчання",[5628,5688,5689,5692],{},[5195,5690,5691],{},"Step Decay:"," зменшення LR у фіксовані епохи з певним фактором",[5628,5694,5695,5698],{},[5195,5696,5697],{},"Cosine Annealing:"," плавне зменшення LR за косинусоїдою",[5628,5700,5701,5704],{},[5195,5702,5703],{},"Warm-up:"," поступове збільшення LR від малого значення на початку навчання",[5628,5706,5707,5710],{},[5195,5708,5709],{},"Learning Rate Restart:"," періодичне скидання LR до початкового значення",[5712,5713],"hr",{},[5186,5715,5717],{"id":5716},"фундамент-як-learning-rate-впливає-на-оптимізацію","Фундамент — як learning rate впливає на оптимізацію",[5191,5719,5720],{},"Перш ніж перейти до schedulers, згадаймо математику оптимізації та візуально зрозуміймо, як LR впливає на траєкторію руху до мінімуму.",[5544,5722,5724],{"id":5723},"оновлення-ваг-у-градієнтному-спуску","Оновлення ваг у градієнтному спуску",[5191,5726,5727],{},"Базова формула SGD (Stochastic Gradient Descent):",[5200,5729],{"tex":5730},"\\mathbf{w}_{t+1} = \\mathbf{w}_t - \\eta \\nabla_{\\mathbf{w}} L(\\mathbf{w}_t)",[5191,5732,5733],{},"Де:",[5625,5735,5736,5745,5753],{},[5628,5737,5738,5741,5742],{},[5200,5739],{"tex":5740,":inline":5203},"\\mathbf{w}_t"," — поточні ваги на кроці ",[5200,5743],{"tex":5744,":inline":5203},"t",[5628,5746,5747,5749,5750,5752],{},[5200,5748],{"tex":5679,":inline":5203}," — ",[5195,5751,5197],{}," (швидкість навчання)",[5628,5754,5755,5758],{},[5200,5756],{"tex":5757,":inline":5203},"\\nabla_{\\mathbf{w}} L"," — градієнт функції втрат",[5191,5760,5761,5764,5765,5767,5768,5771,5772,5774],{},[5195,5762,5763],{},"Ключовий інсайт:"," Learning rate ",[5200,5766],{"tex":5679,":inline":5203}," — це ",[5195,5769,5770],{},"довжина кроку"," у напрямку, протилежному градієнту. Чим більший ",[5200,5773],{"tex":5679,":inline":5203},", тим більший крок робимо за одну ітерацію.",[5544,5776,5778],{"id":5777},"три-сценарії-занадто-малий-оптимальний-занадто-великий-lr","Три сценарії: занадто малий, оптимальний, занадто великий LR",[5191,5780,5781,5782,5785,5786,5789],{},"Розглянемо просту квадратичну функцію втрат ",[5200,5783],{"tex":5784,":inline":5203},"L(w) = (w - 3)^2"," з мінімумом у точці ",[5200,5787],{"tex":5788,":inline":5203},"w^* = 3",".",[5791,5792,5795,5806],"jupyter-notebook",{"kernel":5793,"title":5794},"Python 3.11 (ipykernel)","learning_rate_visualization.ipynb",[5796,5797,5799,5803],"jupyter-cell",{"type":5798},"markdown",[5544,5800,5802],{"id":5801},"візуалізація-впливу-learning-rate","Візуалізація впливу learning rate",[5191,5804,5805],{},"Запустимо градієнтний спуск з трьома різними LR та порівняємо траєкторії.",[5796,5807,5810,7106],{"execution-count":5808,"execution-time":5809},"1","0.92s",[5237,5811,5815],{"className":5812,"code":5813,"language":5814,"meta":5242,"style":5242},"language-python shiki shiki-themes light-plus dark-plus dark-plus","import numpy as np\nimport matplotlib.pyplot as plt\n\n# Проста квадратична функція: L(w) = (w - 3)²\ndef loss_fn(w):\n    return (w - 3) ** 2\n\ndef gradient(w):\n    return 2 * (w - 3)\n\n# Градієнтний спуск з різними LR\ndef gradient_descent(w_init, lr, num_steps):\n    trajectory = [w_init]\n    w = w_init\n    \n    for _ in range(num_steps):\n        grad = gradient(w)\n        w = w - lr * grad\n        trajectory.append(w)\n    \n    return np.array(trajectory)\n\n# Три сценарії\nw_init = 0.0\nnum_steps = 15\n\ntraj_small = gradient_descent(w_init, lr=0.1, num_steps=num_steps)    # Малий LR\ntraj_optimal = gradient_descent(w_init, lr=0.5, num_steps=num_steps)  # Оптимальний LR\ntraj_large = gradient_descent(w_init, lr=1.1, num_steps=num_steps)    # Занадто великий LR\n\n# Візуалізація\nfig, axes = plt.subplots(1, 3, figsize=(18, 5))\n\n# Функція втрат\nw_range = np.linspace(-1, 6, 200)\nloss_range = loss_fn(w_range)\n\nscenarios = [\n    (traj_small, 0.1, 'Занадто малий LR = 0.1', '#3b82f6', axes[0]),\n    (traj_optimal, 0.5, 'Оптимальний LR = 0.5', '#22c55e', axes[1]),\n    (traj_large, 1.1, 'Занадто великий LR = 1.1', '#ef4444', axes[2])\n]\n\nfor trajectory, lr, title, color, ax in scenarios:\n    # Ландшафт втрат\n    ax.plot(w_range, loss_range, 'k-', linewidth=1.5, alpha=0.3, label='Loss landscape')\n    \n    # Мінімум\n    ax.plot(3, 0, 'g*', markersize=20, label='Глобальний мінімум', zorder=5)\n    \n    # Траєкторія оптимізації\n    losses = loss_fn(trajectory)\n    ax.plot(trajectory, losses, 'o-', color=color, linewidth=2.5, \n            markersize=6, alpha=0.8, label='Траєкторія GD')\n    \n    # Стартова точка\n    ax.plot(trajectory[0], losses[0], 'ko', markersize=12, label='Старт', zorder=4)\n    \n    # Нумерація кроків\n    for i in [0, 5, 10, min(14, len(trajectory)-1)]:\n        if i \u003C len(trajectory):\n            ax.annotate(f'{i}', xy=(trajectory[i], losses[i]), \n                       xytext=(5, 5), textcoords='offset points', fontsize=9)\n    \n    ax.set_xlabel('Weight (w)', fontsize=12)\n    ax.set_ylabel('Loss L(w)', fontsize=12)\n    ax.set_title(title, fontsize=13, fontweight='bold')\n    ax.legend(fontsize=9)\n    ax.grid(alpha=0.3)\n    ax.set_ylim([-1, 15])\n\nplt.tight_layout()\nplt.show()\n\n# Виведення статистики\nprint(\"📊 Порівняння конвергенції:\\n\")\nprint(f\"{'LR':\u003C8} {'Кроків до w ≈ 3':\u003C20} {'Фінальне w':\u003C15} {'Фінальна втрата':\u003C20} {'Статус'}\")\nprint(\"-\" * 85)\n\nfor traj, lr, desc, _, _ in scenarios:\n    final_w = traj[-1]\n    final_loss = loss_fn(final_w)\n    \n    # Скільки кроків потрібно, щоб досягти |w - 3| \u003C 0.1\n    converged_step = None\n    for i, w in enumerate(traj):\n        if abs(w - 3) \u003C 0.1:\n            converged_step = i\n            break\n    \n    status = \"✅ Сходиться\" if converged_step else \"❌ Не сходиться\"\n    steps_str = f\"{converged_step}\" if converged_step else \"—\"\n    \n    print(f\"{lr:\u003C8.1f} {steps_str:\u003C20} {final_w:\u003C15.4f} {final_loss:\u003C20.6f} {status}\")\n","python",[5244,5816,5817,5833,5845,5849,5855,5875,5893,5897,5910,5925,5929,5934,5959,5964,5969,5974,5991,5996,6001,6006,6010,6017,6021,6026,6034,6042,6046,6069,6091,6112,6116,6121,6151,6155,6160,6179,6184,6188,6193,6220,6243,6268,6273,6277,6290,6295,6335,6339,6344,6390,6394,6399,6405,6432,6462,6467,6473,6521,6526,6532,6579,6593,6624,6661,6666,6685,6704,6729,6743,6757,6772,6777,6783,6789,6794,6800,6820,6874,6892,6897,6909,6919,6925,6930,6936,6945,6961,6982,6988,6994,6999,7020,7048,7053],{"__ignoreMap":5242},[5247,5818,5819,5823,5827,5830],{"class":5249,"line":5250},[5247,5820,5822],{"class":5821},"s8xlr","import",[5247,5824,5826],{"class":5825},"sHH4Y"," numpy ",[5247,5828,5829],{"class":5821},"as",[5247,5831,5832],{"class":5825}," np\n",[5247,5834,5835,5837,5840,5842],{"class":5249,"line":5256},[5247,5836,5822],{"class":5821},[5247,5838,5839],{"class":5825}," matplotlib.pyplot ",[5247,5841,5829],{"class":5821},[5247,5843,5844],{"class":5825}," plt\n",[5247,5846,5847],{"class":5249,"line":5262},[5247,5848,5278],{"emptyLinePlaceholder":5277},[5247,5850,5851],{"class":5249,"line":5268},[5247,5852,5854],{"class":5853},"spJ8K","# Проста квадратична функція: L(w) = (w - 3)²\n",[5247,5856,5857,5861,5865,5868,5872],{"class":5249,"line":5274},[5247,5858,5860],{"class":5859},"su1O8","def",[5247,5862,5864],{"class":5863},"s8Opu"," loss_fn",[5247,5866,5867],{"class":5825},"(",[5247,5869,5871],{"class":5870},"siwwj","w",[5247,5873,5874],{"class":5825},"):\n",[5247,5876,5877,5880,5883,5887,5890],{"class":5249,"line":5281},[5247,5878,5879],{"class":5821},"    return",[5247,5881,5882],{"class":5825}," (w - ",[5247,5884,5886],{"class":5885},"sJj4R","3",[5247,5888,5889],{"class":5825},") ** ",[5247,5891,5892],{"class":5885},"2\n",[5247,5894,5895],{"class":5249,"line":5287},[5247,5896,5278],{"emptyLinePlaceholder":5277},[5247,5898,5899,5901,5904,5906,5908],{"class":5249,"line":5293},[5247,5900,5860],{"class":5859},[5247,5902,5903],{"class":5863}," gradient",[5247,5905,5867],{"class":5825},[5247,5907,5871],{"class":5870},[5247,5909,5874],{"class":5825},[5247,5911,5912,5914,5917,5920,5922],{"class":5249,"line":5299},[5247,5913,5879],{"class":5821},[5247,5915,5916],{"class":5885}," 2",[5247,5918,5919],{"class":5825}," * (w - ",[5247,5921,5886],{"class":5885},[5247,5923,5924],{"class":5825},")\n",[5247,5926,5927],{"class":5249,"line":5304},[5247,5928,5278],{"emptyLinePlaceholder":5277},[5247,5930,5931],{"class":5249,"line":5310},[5247,5932,5933],{"class":5853},"# Градієнтний спуск з різними LR\n",[5247,5935,5936,5938,5941,5943,5946,5949,5952,5954,5957],{"class":5249,"line":5316},[5247,5937,5860],{"class":5859},[5247,5939,5940],{"class":5863}," gradient_descent",[5247,5942,5867],{"class":5825},[5247,5944,5945],{"class":5870},"w_init",[5247,5947,5948],{"class":5825},", ",[5247,5950,5951],{"class":5870},"lr",[5247,5953,5948],{"class":5825},[5247,5955,5956],{"class":5870},"num_steps",[5247,5958,5874],{"class":5825},[5247,5960,5961],{"class":5249,"line":5322},[5247,5962,5963],{"class":5825},"    trajectory = [w_init]\n",[5247,5965,5966],{"class":5249,"line":5328},[5247,5967,5968],{"class":5825},"    w = w_init\n",[5247,5970,5971],{"class":5249,"line":5334},[5247,5972,5973],{"class":5825},"    \n",[5247,5975,5976,5979,5982,5985,5988],{"class":5249,"line":5340},[5247,5977,5978],{"class":5821},"    for",[5247,5980,5981],{"class":5825}," _ ",[5247,5983,5984],{"class":5821},"in",[5247,5986,5987],{"class":5863}," range",[5247,5989,5990],{"class":5825},"(num_steps):\n",[5247,5992,5993],{"class":5249,"line":5346},[5247,5994,5995],{"class":5825},"        grad = gradient(w)\n",[5247,5997,5998],{"class":5249,"line":5352},[5247,5999,6000],{"class":5825},"        w = w - lr * grad\n",[5247,6002,6003],{"class":5249,"line":5358},[5247,6004,6005],{"class":5825},"        trajectory.append(w)\n",[5247,6007,6008],{"class":5249,"line":5364},[5247,6009,5973],{"class":5825},[5247,6011,6012,6014],{"class":5249,"line":5369},[5247,6013,5879],{"class":5821},[5247,6015,6016],{"class":5825}," np.array(trajectory)\n",[5247,6018,6019],{"class":5249,"line":5375},[5247,6020,5278],{"emptyLinePlaceholder":5277},[5247,6022,6023],{"class":5249,"line":5380},[5247,6024,6025],{"class":5853},"# Три сценарії\n",[5247,6027,6028,6031],{"class":5249,"line":5386},[5247,6029,6030],{"class":5825},"w_init = ",[5247,6032,6033],{"class":5885},"0.0\n",[5247,6035,6036,6039],{"class":5249,"line":5392},[5247,6037,6038],{"class":5825},"num_steps = ",[5247,6040,6041],{"class":5885},"15\n",[5247,6043,6044],{"class":5249,"line":5398},[5247,6045,5278],{"emptyLinePlaceholder":5277},[5247,6047,6048,6051,6053,6056,6059,6061,6063,6066],{"class":5249,"line":5404},[5247,6049,6050],{"class":5825},"traj_small = gradient_descent(w_init, ",[5247,6052,5951],{"class":5870},[5247,6054,6055],{"class":5825},"=",[5247,6057,6058],{"class":5885},"0.1",[5247,6060,5948],{"class":5825},[5247,6062,5956],{"class":5870},[5247,6064,6065],{"class":5825},"=num_steps)    ",[5247,6067,6068],{"class":5853},"# Малий LR\n",[5247,6070,6071,6074,6076,6078,6081,6083,6085,6088],{"class":5249,"line":5409},[5247,6072,6073],{"class":5825},"traj_optimal = gradient_descent(w_init, ",[5247,6075,5951],{"class":5870},[5247,6077,6055],{"class":5825},[5247,6079,6080],{"class":5885},"0.5",[5247,6082,5948],{"class":5825},[5247,6084,5956],{"class":5870},[5247,6086,6087],{"class":5825},"=num_steps)  ",[5247,6089,6090],{"class":5853},"# Оптимальний LR\n",[5247,6092,6093,6096,6098,6100,6103,6105,6107,6109],{"class":5249,"line":5414},[5247,6094,6095],{"class":5825},"traj_large = gradient_descent(w_init, ",[5247,6097,5951],{"class":5870},[5247,6099,6055],{"class":5825},[5247,6101,6102],{"class":5885},"1.1",[5247,6104,5948],{"class":5825},[5247,6106,5956],{"class":5870},[5247,6108,6065],{"class":5825},[5247,6110,6111],{"class":5853},"# Занадто великий LR\n",[5247,6113,6114],{"class":5249,"line":5419},[5247,6115,5278],{"emptyLinePlaceholder":5277},[5247,6117,6118],{"class":5249,"line":5425},[5247,6119,6120],{"class":5853},"# Візуалізація\n",[5247,6122,6123,6126,6128,6130,6132,6134,6137,6140,6143,6145,6148],{"class":5249,"line":5430},[5247,6124,6125],{"class":5825},"fig, axes = plt.subplots(",[5247,6127,5808],{"class":5885},[5247,6129,5948],{"class":5825},[5247,6131,5886],{"class":5885},[5247,6133,5948],{"class":5825},[5247,6135,6136],{"class":5870},"figsize",[5247,6138,6139],{"class":5825},"=(",[5247,6141,6142],{"class":5885},"18",[5247,6144,5948],{"class":5825},[5247,6146,6147],{"class":5885},"5",[5247,6149,6150],{"class":5825},"))\n",[5247,6152,6153],{"class":5249,"line":5436},[5247,6154,5278],{"emptyLinePlaceholder":5277},[5247,6156,6157],{"class":5249,"line":5442},[5247,6158,6159],{"class":5853},"# Функція втрат\n",[5247,6161,6162,6165,6167,6169,6172,6174,6177],{"class":5249,"line":5448},[5247,6163,6164],{"class":5825},"w_range = np.linspace(-",[5247,6166,5808],{"class":5885},[5247,6168,5948],{"class":5825},[5247,6170,6171],{"class":5885},"6",[5247,6173,5948],{"class":5825},[5247,6175,6176],{"class":5885},"200",[5247,6178,5924],{"class":5825},[5247,6180,6181],{"class":5249,"line":5454},[5247,6182,6183],{"class":5825},"loss_range = loss_fn(w_range)\n",[5247,6185,6186],{"class":5249,"line":5460},[5247,6187,5278],{"emptyLinePlaceholder":5277},[5247,6189,6190],{"class":5249,"line":5466},[5247,6191,6192],{"class":5825},"scenarios = [\n",[5247,6194,6195,6198,6200,6202,6206,6208,6211,6214,6217],{"class":5249,"line":5472},[5247,6196,6197],{"class":5825},"    (traj_small, ",[5247,6199,6058],{"class":5885},[5247,6201,5948],{"class":5825},[5247,6203,6205],{"class":6204},"sbdoH","'Занадто малий LR = 0.1'",[5247,6207,5948],{"class":5825},[5247,6209,6210],{"class":6204},"'#3b82f6'",[5247,6212,6213],{"class":5825},", axes[",[5247,6215,6216],{"class":5885},"0",[5247,6218,6219],{"class":5825},"]),\n",[5247,6221,6222,6225,6227,6229,6232,6234,6237,6239,6241],{"class":5249,"line":5477},[5247,6223,6224],{"class":5825},"    (traj_optimal, ",[5247,6226,6080],{"class":5885},[5247,6228,5948],{"class":5825},[5247,6230,6231],{"class":6204},"'Оптимальний LR = 0.5'",[5247,6233,5948],{"class":5825},[5247,6235,6236],{"class":6204},"'#22c55e'",[5247,6238,6213],{"class":5825},[5247,6240,5808],{"class":5885},[5247,6242,6219],{"class":5825},[5247,6244,6245,6248,6250,6252,6255,6257,6260,6262,6265],{"class":5249,"line":5482},[5247,6246,6247],{"class":5825},"    (traj_large, ",[5247,6249,6102],{"class":5885},[5247,6251,5948],{"class":5825},[5247,6253,6254],{"class":6204},"'Занадто великий LR = 1.1'",[5247,6256,5948],{"class":5825},[5247,6258,6259],{"class":6204},"'#ef4444'",[5247,6261,6213],{"class":5825},[5247,6263,6264],{"class":5885},"2",[5247,6266,6267],{"class":5825},"])\n",[5247,6269,6270],{"class":5249,"line":5488},[5247,6271,6272],{"class":5825},"]\n",[5247,6274,6275],{"class":5249,"line":5493},[5247,6276,5278],{"emptyLinePlaceholder":5277},[5247,6278,6279,6282,6285,6287],{"class":5249,"line":5499},[5247,6280,6281],{"class":5821},"for",[5247,6283,6284],{"class":5825}," trajectory, lr, title, color, ax ",[5247,6286,5984],{"class":5821},[5247,6288,6289],{"class":5825}," scenarios:\n",[5247,6291,6292],{"class":5249,"line":5505},[5247,6293,6294],{"class":5853},"    # Ландшафт втрат\n",[5247,6296,6297,6300,6303,6305,6308,6310,6313,6315,6318,6320,6323,6325,6328,6330,6333],{"class":5249,"line":5510},[5247,6298,6299],{"class":5825},"    ax.plot(w_range, loss_range, ",[5247,6301,6302],{"class":6204},"'k-'",[5247,6304,5948],{"class":5825},[5247,6306,6307],{"class":5870},"linewidth",[5247,6309,6055],{"class":5825},[5247,6311,6312],{"class":5885},"1.5",[5247,6314,5948],{"class":5825},[5247,6316,6317],{"class":5870},"alpha",[5247,6319,6055],{"class":5825},[5247,6321,6322],{"class":5885},"0.3",[5247,6324,5948],{"class":5825},[5247,6326,6327],{"class":5870},"label",[5247,6329,6055],{"class":5825},[5247,6331,6332],{"class":6204},"'Loss landscape'",[5247,6334,5924],{"class":5825},[5247,6336,6337],{"class":5249,"line":5516},[5247,6338,5973],{"class":5825},[5247,6340,6341],{"class":5249,"line":5522},[5247,6342,6343],{"class":5853},"    # Мінімум\n",[5247,6345,6346,6349,6351,6353,6355,6357,6360,6362,6365,6367,6370,6372,6374,6376,6379,6381,6384,6386,6388],{"class":5249,"line":5528},[5247,6347,6348],{"class":5825},"    ax.plot(",[5247,6350,5886],{"class":5885},[5247,6352,5948],{"class":5825},[5247,6354,6216],{"class":5885},[5247,6356,5948],{"class":5825},[5247,6358,6359],{"class":6204},"'g*'",[5247,6361,5948],{"class":5825},[5247,6363,6364],{"class":5870},"markersize",[5247,6366,6055],{"class":5825},[5247,6368,6369],{"class":5885},"20",[5247,6371,5948],{"class":5825},[5247,6373,6327],{"class":5870},[5247,6375,6055],{"class":5825},[5247,6377,6378],{"class":6204},"'Глобальний мінімум'",[5247,6380,5948],{"class":5825},[5247,6382,6383],{"class":5870},"zorder",[5247,6385,6055],{"class":5825},[5247,6387,6147],{"class":5885},[5247,6389,5924],{"class":5825},[5247,6391,6392],{"class":5249,"line":5534},[5247,6393,5973],{"class":5825},[5247,6395,6396],{"class":5249,"line":5539},[5247,6397,6398],{"class":5853},"    # Траєкторія оптимізації\n",[5247,6400,6402],{"class":5249,"line":6401},52,[5247,6403,6404],{"class":5825},"    losses = loss_fn(trajectory)\n",[5247,6406,6408,6411,6414,6416,6419,6422,6424,6426,6429],{"class":5249,"line":6407},53,[5247,6409,6410],{"class":5825},"    ax.plot(trajectory, losses, ",[5247,6412,6413],{"class":6204},"'o-'",[5247,6415,5948],{"class":5825},[5247,6417,6418],{"class":5870},"color",[5247,6420,6421],{"class":5825},"=color, ",[5247,6423,6307],{"class":5870},[5247,6425,6055],{"class":5825},[5247,6427,6428],{"class":5885},"2.5",[5247,6430,6431],{"class":5825},", \n",[5247,6433,6435,6438,6440,6442,6444,6446,6448,6451,6453,6455,6457,6460],{"class":5249,"line":6434},54,[5247,6436,6437],{"class":5870},"            markersize",[5247,6439,6055],{"class":5825},[5247,6441,6171],{"class":5885},[5247,6443,5948],{"class":5825},[5247,6445,6317],{"class":5870},[5247,6447,6055],{"class":5825},[5247,6449,6450],{"class":5885},"0.8",[5247,6452,5948],{"class":5825},[5247,6454,6327],{"class":5870},[5247,6456,6055],{"class":5825},[5247,6458,6459],{"class":6204},"'Траєкторія GD'",[5247,6461,5924],{"class":5825},[5247,6463,6465],{"class":5249,"line":6464},55,[5247,6466,5973],{"class":5825},[5247,6468,6470],{"class":5249,"line":6469},56,[5247,6471,6472],{"class":5853},"    # Стартова точка\n",[5247,6474,6476,6479,6481,6484,6486,6489,6492,6494,6496,6498,6501,6503,6505,6507,6510,6512,6514,6516,6519],{"class":5249,"line":6475},57,[5247,6477,6478],{"class":5825},"    ax.plot(trajectory[",[5247,6480,6216],{"class":5885},[5247,6482,6483],{"class":5825},"], losses[",[5247,6485,6216],{"class":5885},[5247,6487,6488],{"class":5825},"], ",[5247,6490,6491],{"class":6204},"'ko'",[5247,6493,5948],{"class":5825},[5247,6495,6364],{"class":5870},[5247,6497,6055],{"class":5825},[5247,6499,6500],{"class":5885},"12",[5247,6502,5948],{"class":5825},[5247,6504,6327],{"class":5870},[5247,6506,6055],{"class":5825},[5247,6508,6509],{"class":6204},"'Старт'",[5247,6511,5948],{"class":5825},[5247,6513,6383],{"class":5870},[5247,6515,6055],{"class":5825},[5247,6517,6518],{"class":5885},"4",[5247,6520,5924],{"class":5825},[5247,6522,6524],{"class":5249,"line":6523},58,[5247,6525,5973],{"class":5825},[5247,6527,6529],{"class":5249,"line":6528},59,[5247,6530,6531],{"class":5853},"    # Нумерація кроків\n",[5247,6533,6535,6537,6540,6542,6545,6547,6549,6551,6553,6556,6558,6561,6563,6566,6568,6571,6574,6576],{"class":5249,"line":6534},60,[5247,6536,5978],{"class":5821},[5247,6538,6539],{"class":5825}," i ",[5247,6541,5984],{"class":5821},[5247,6543,6544],{"class":5825}," [",[5247,6546,6216],{"class":5885},[5247,6548,5948],{"class":5825},[5247,6550,6147],{"class":5885},[5247,6552,5948],{"class":5825},[5247,6554,6555],{"class":5885},"10",[5247,6557,5948],{"class":5825},[5247,6559,6560],{"class":5863},"min",[5247,6562,5867],{"class":5825},[5247,6564,6565],{"class":5885},"14",[5247,6567,5948],{"class":5825},[5247,6569,6570],{"class":5863},"len",[5247,6572,6573],{"class":5825},"(trajectory)-",[5247,6575,5808],{"class":5885},[5247,6577,6578],{"class":5825},")]:\n",[5247,6580,6582,6585,6588,6590],{"class":5249,"line":6581},61,[5247,6583,6584],{"class":5821},"        if",[5247,6586,6587],{"class":5825}," i \u003C ",[5247,6589,6570],{"class":5863},[5247,6591,6592],{"class":5825},"(trajectory):\n",[5247,6594,6596,6599,6602,6605,6608,6611,6614,6616,6618,6621],{"class":5249,"line":6595},62,[5247,6597,6598],{"class":5825},"            ax.annotate(",[5247,6600,6601],{"class":5859},"f",[5247,6603,6604],{"class":6204},"'",[5247,6606,6607],{"class":5859},"{",[5247,6609,6610],{"class":5825},"i",[5247,6612,6613],{"class":5859},"}",[5247,6615,6604],{"class":6204},[5247,6617,5948],{"class":5825},[5247,6619,6620],{"class":5870},"xy",[5247,6622,6623],{"class":5825},"=(trajectory[i], losses[i]), \n",[5247,6625,6627,6630,6632,6634,6636,6638,6641,6644,6646,6649,6651,6654,6656,6659],{"class":5249,"line":6626},63,[5247,6628,6629],{"class":5870},"                       xytext",[5247,6631,6139],{"class":5825},[5247,6633,6147],{"class":5885},[5247,6635,5948],{"class":5825},[5247,6637,6147],{"class":5885},[5247,6639,6640],{"class":5825},"), ",[5247,6642,6643],{"class":5870},"textcoords",[5247,6645,6055],{"class":5825},[5247,6647,6648],{"class":6204},"'offset points'",[5247,6650,5948],{"class":5825},[5247,6652,6653],{"class":5870},"fontsize",[5247,6655,6055],{"class":5825},[5247,6657,6658],{"class":5885},"9",[5247,6660,5924],{"class":5825},[5247,6662,6664],{"class":5249,"line":6663},64,[5247,6665,5973],{"class":5825},[5247,6667,6669,6672,6675,6677,6679,6681,6683],{"class":5249,"line":6668},65,[5247,6670,6671],{"class":5825},"    ax.set_xlabel(",[5247,6673,6674],{"class":6204},"'Weight (w)'",[5247,6676,5948],{"class":5825},[5247,6678,6653],{"class":5870},[5247,6680,6055],{"class":5825},[5247,6682,6500],{"class":5885},[5247,6684,5924],{"class":5825},[5247,6686,6688,6691,6694,6696,6698,6700,6702],{"class":5249,"line":6687},66,[5247,6689,6690],{"class":5825},"    ax.set_ylabel(",[5247,6692,6693],{"class":6204},"'Loss L(w)'",[5247,6695,5948],{"class":5825},[5247,6697,6653],{"class":5870},[5247,6699,6055],{"class":5825},[5247,6701,6500],{"class":5885},[5247,6703,5924],{"class":5825},[5247,6705,6707,6710,6712,6714,6717,6719,6722,6724,6727],{"class":5249,"line":6706},67,[5247,6708,6709],{"class":5825},"    ax.set_title(title, ",[5247,6711,6653],{"class":5870},[5247,6713,6055],{"class":5825},[5247,6715,6716],{"class":5885},"13",[5247,6718,5948],{"class":5825},[5247,6720,6721],{"class":5870},"fontweight",[5247,6723,6055],{"class":5825},[5247,6725,6726],{"class":6204},"'bold'",[5247,6728,5924],{"class":5825},[5247,6730,6732,6735,6737,6739,6741],{"class":5249,"line":6731},68,[5247,6733,6734],{"class":5825},"    ax.legend(",[5247,6736,6653],{"class":5870},[5247,6738,6055],{"class":5825},[5247,6740,6658],{"class":5885},[5247,6742,5924],{"class":5825},[5247,6744,6746,6749,6751,6753,6755],{"class":5249,"line":6745},69,[5247,6747,6748],{"class":5825},"    ax.grid(",[5247,6750,6317],{"class":5870},[5247,6752,6055],{"class":5825},[5247,6754,6322],{"class":5885},[5247,6756,5924],{"class":5825},[5247,6758,6760,6763,6765,6767,6770],{"class":5249,"line":6759},70,[5247,6761,6762],{"class":5825},"    ax.set_ylim([-",[5247,6764,5808],{"class":5885},[5247,6766,5948],{"class":5825},[5247,6768,6769],{"class":5885},"15",[5247,6771,6267],{"class":5825},[5247,6773,6775],{"class":5249,"line":6774},71,[5247,6776,5278],{"emptyLinePlaceholder":5277},[5247,6778,6780],{"class":5249,"line":6779},72,[5247,6781,6782],{"class":5825},"plt.tight_layout()\n",[5247,6784,6786],{"class":5249,"line":6785},73,[5247,6787,6788],{"class":5825},"plt.show()\n",[5247,6790,6792],{"class":5249,"line":6791},74,[5247,6793,5278],{"emptyLinePlaceholder":5277},[5247,6795,6797],{"class":5249,"line":6796},75,[5247,6798,6799],{"class":5853},"# Виведення статистики\n",[5247,6801,6803,6806,6808,6811,6815,6818],{"class":5249,"line":6802},76,[5247,6804,6805],{"class":5863},"print",[5247,6807,5867],{"class":5825},[5247,6809,6810],{"class":6204},"\"📊 Порівняння конвергенції:",[5247,6812,6814],{"class":6813},"sjcCO","\\n",[5247,6816,6817],{"class":6204},"\"",[5247,6819,5924],{"class":5825},[5247,6821,6823,6825,6827,6829,6831,6833,6836,6839,6842,6845,6848,6850,6853,6856,6858,6861,6863,6865,6868,6870,6872],{"class":5249,"line":6822},77,[5247,6824,6805],{"class":5863},[5247,6826,5867],{"class":5825},[5247,6828,6601],{"class":5859},[5247,6830,6817],{"class":6204},[5247,6832,6607],{"class":5859},[5247,6834,6835],{"class":6204},"'LR'",[5247,6837,6838],{"class":5859},":\u003C8}",[5247,6840,6841],{"class":5859}," {",[5247,6843,6844],{"class":6204},"'Кроків до w ≈ 3'",[5247,6846,6847],{"class":5859},":\u003C20}",[5247,6849,6841],{"class":5859},[5247,6851,6852],{"class":6204},"'Фінальне w'",[5247,6854,6855],{"class":5859},":\u003C15}",[5247,6857,6841],{"class":5859},[5247,6859,6860],{"class":6204},"'Фінальна втрата'",[5247,6862,6847],{"class":5859},[5247,6864,6841],{"class":5859},[5247,6866,6867],{"class":6204},"'Статус'",[5247,6869,6613],{"class":5859},[5247,6871,6817],{"class":6204},[5247,6873,5924],{"class":5825},[5247,6875,6877,6879,6881,6884,6887,6890],{"class":5249,"line":6876},78,[5247,6878,6805],{"class":5863},[5247,6880,5867],{"class":5825},[5247,6882,6883],{"class":6204},"\"-\"",[5247,6885,6886],{"class":5825}," * ",[5247,6888,6889],{"class":5885},"85",[5247,6891,5924],{"class":5825},[5247,6893,6895],{"class":5249,"line":6894},79,[5247,6896,5278],{"emptyLinePlaceholder":5277},[5247,6898,6900,6902,6905,6907],{"class":5249,"line":6899},80,[5247,6901,6281],{"class":5821},[5247,6903,6904],{"class":5825}," traj, lr, desc, _, _ ",[5247,6906,5984],{"class":5821},[5247,6908,6289],{"class":5825},[5247,6910,6912,6915,6917],{"class":5249,"line":6911},81,[5247,6913,6914],{"class":5825},"    final_w = traj[-",[5247,6916,5808],{"class":5885},[5247,6918,6272],{"class":5825},[5247,6920,6922],{"class":5249,"line":6921},82,[5247,6923,6924],{"class":5825},"    final_loss = loss_fn(final_w)\n",[5247,6926,6928],{"class":5249,"line":6927},83,[5247,6929,5973],{"class":5825},[5247,6931,6933],{"class":5249,"line":6932},84,[5247,6934,6935],{"class":5853},"    # Скільки кроків потрібно, щоб досягти |w - 3| \u003C 0.1\n",[5247,6937,6939,6942],{"class":5249,"line":6938},85,[5247,6940,6941],{"class":5825},"    converged_step = ",[5247,6943,6944],{"class":5859},"None\n",[5247,6946,6948,6950,6953,6955,6958],{"class":5249,"line":6947},86,[5247,6949,5978],{"class":5821},[5247,6951,6952],{"class":5825}," i, w ",[5247,6954,5984],{"class":5821},[5247,6956,6957],{"class":5863}," enumerate",[5247,6959,6960],{"class":5825},"(traj):\n",[5247,6962,6964,6966,6969,6972,6974,6977,6979],{"class":5249,"line":6963},87,[5247,6965,6584],{"class":5821},[5247,6967,6968],{"class":5863}," abs",[5247,6970,6971],{"class":5825},"(w - ",[5247,6973,5886],{"class":5885},[5247,6975,6976],{"class":5825},") \u003C ",[5247,6978,6058],{"class":5885},[5247,6980,6981],{"class":5825},":\n",[5247,6983,6985],{"class":5249,"line":6984},88,[5247,6986,6987],{"class":5825},"            converged_step = i\n",[5247,6989,6991],{"class":5249,"line":6990},89,[5247,6992,6993],{"class":5821},"            break\n",[5247,6995,6997],{"class":5249,"line":6996},90,[5247,6998,5973],{"class":5825},[5247,7000,7002,7005,7008,7011,7014,7017],{"class":5249,"line":7001},91,[5247,7003,7004],{"class":5825},"    status = ",[5247,7006,7007],{"class":6204},"\"✅ Сходиться\"",[5247,7009,7010],{"class":5821}," if",[5247,7012,7013],{"class":5825}," converged_step ",[5247,7015,7016],{"class":5821},"else",[5247,7018,7019],{"class":6204}," \"❌ Не сходиться\"\n",[5247,7021,7023,7026,7028,7030,7032,7035,7037,7039,7041,7043,7045],{"class":5249,"line":7022},92,[5247,7024,7025],{"class":5825},"    steps_str = ",[5247,7027,6601],{"class":5859},[5247,7029,6817],{"class":6204},[5247,7031,6607],{"class":5859},[5247,7033,7034],{"class":5825},"converged_step",[5247,7036,6613],{"class":5859},[5247,7038,6817],{"class":6204},[5247,7040,7010],{"class":5821},[5247,7042,7013],{"class":5825},[5247,7044,7016],{"class":5821},[5247,7046,7047],{"class":6204}," \"—\"\n",[5247,7049,7051],{"class":5249,"line":7050},93,[5247,7052,5973],{"class":5825},[5247,7054,7056,7059,7061,7063,7065,7067,7069,7072,7074,7077,7079,7081,7084,7087,7089,7092,7095,7097,7100,7102,7104],{"class":5249,"line":7055},94,[5247,7057,7058],{"class":5863},"    print",[5247,7060,5867],{"class":5825},[5247,7062,6601],{"class":5859},[5247,7064,6817],{"class":6204},[5247,7066,6607],{"class":5859},[5247,7068,5951],{"class":5825},[5247,7070,7071],{"class":5859},":\u003C8.1f}",[5247,7073,6841],{"class":5859},[5247,7075,7076],{"class":5825},"steps_str",[5247,7078,6847],{"class":5859},[5247,7080,6841],{"class":5859},[5247,7082,7083],{"class":5825},"final_w",[5247,7085,7086],{"class":5859},":\u003C15.4f}",[5247,7088,6841],{"class":5859},[5247,7090,7091],{"class":5825},"final_loss",[5247,7093,7094],{"class":5859},":\u003C20.6f}",[5247,7096,6841],{"class":5859},[5247,7098,7099],{"class":5825},"status",[5247,7101,6613],{"class":5859},[5247,7103,6817],{"class":6204},[5247,7105,5924],{"class":5825},[7107,7108,7109,7118,7124],"template",{"v-slot:output":5242},[5191,7110,7111],{},[7112,7113],"img",{"alt":7114,"className":7115,"src":7117},"Вплив learning rate на конвергенцію: малий LR — повільно, оптимальний — швидко, великий — дивергенція",[7116],"diagram-img","\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling\u002F01.png",[5191,7119,7120,7121],{},"📊 ",[5195,7122,7123],{},"Порівняння конвергенції:",[7125,7126,7127,7150],"table",{},[7128,7129,7130],"thead",{},[7131,7132,7133,7138,7141,7144,7147],"tr",{},[7134,7135,7137],"th",{"align":7136},"left","LR",[7134,7139,7140],{"align":7136},"Кроків до w ≈ 3",[7134,7142,7143],{"align":7136},"Фінальне w",[7134,7145,7146],{"align":7136},"Фінальна втрата",[7134,7148,7149],{"align":7136},"Статус",[7151,7152,7153,7172,7190],"tbody",{},[7131,7154,7155,7158,7160,7163,7166],{},[7156,7157,6058],"td",{"align":7136},[7156,7159,6716],{"align":7136},[7156,7161,7162],{"align":7136},"2.9135",[7156,7164,7165],{"align":7136},"0.007479",[7156,7167,7168,7169],{"align":7136},"✅ Сходиться, але ",[5195,7170,7171],{},"повільно",[7131,7173,7174,7176,7178,7181,7184],{},[7156,7175,6080],{"align":7136},[7156,7177,6518],{"align":7136},[7156,7179,7180],{"align":7136},"3.0000",[7156,7182,7183],{"align":7136},"0.000000",[7156,7185,7186,7187],{"align":7136},"✅ Сходиться ",[5195,7188,7189],{},"оптимально",[7131,7191,7192,7194,7197,7200,7203],{},[7156,7193,6102],{"align":7136},[7156,7195,7196],{"align":7136},"—",[7156,7198,7199],{"align":7136},"-5.8645",[7156,7201,7202],{"align":7136},"78.180021",[7156,7204,7205,7206,7209],{"align":7136},"❌ ",[5195,7207,7208],{},"Дивергенція"," (відлітає у -∞)",[7211,7212,7213,7218],"note",{},[5191,7214,7215],{},[5195,7216,7217],{},"Інтерпретація результатів:",[5625,7219,7220,7230,7240],{},[5628,7221,7222,7225,7226,7229],{},[5195,7223,7224],{},"LR = 0.1 (малий):"," Модель повільно, але впевнено рухається до мінімуму. Потрібно 13 кроків. Фінальна втрата близька до нуля, але не ідеальна. ",[5195,7227,7228],{},"Проблема:"," Навчання займе багато часу, особливо для глибоких мереж.",[5628,7231,7232,7235,7236,7239],{},[5195,7233,7234],{},"LR = 0.5 (оптимальний):"," Швидка та стабільна конвергенція за 4 кроки. Фінальна втрата практично нульова. ",[5195,7237,7238],{},"Ідеальний баланс"," між швидкістю та стабільністю.",[5628,7241,7242,7245,7246,7249,7250,7253],{},[5195,7243,7244],{},"LR = 1.1 (великий):"," Катастрофа! Модель ",[5195,7247,7248],{},"перестрибує"," через мінімум з кожним кроком, рухаючись все далі. Втрати ",[5195,7251,7252],{},"зростають"," замість зменшення. Навчання нестабільне, градієнти можуть вибухнути (exploding gradients).",[5544,7255,7257],{"id":7256},"проблема-у-реальних-нейронних-мережах","Проблема у реальних нейронних мережах",[5191,7259,7260,7261,7264],{},"У реальних глибоких мережах ландшафт втрат ",[5195,7262,7263],{},"набагато складніший"," за просту квадратичну функцію:",[5209,7266,7267,7280,7301],{},[5212,7268,7271,7274],{"icon":7269,"title":7270},"i-lucide-mountain-snow","🏔️ Нерівномірна кривизна",[5191,7272,7273],{},"Різні напрямки у просторі параметрів мають різну \"крутизну\". У одному напрямку градієнт крутий (потрібен малий LR), в іншому — пологий (потрібен великий LR).",[5191,7275,7276,7279],{},[5195,7277,7278],{},"Наслідок:"," Один фіксований LR не може бути оптимальним для всіх напрямків.",[5212,7281,7284,7295],{"icon":7282,"title":7283},"i-lucide-trending-up","🎢 Сідлові точки та плато",[5191,7285,7286,7287,7290,7291,7294],{},"Ландшафт містить ",[5195,7288,7289],{},"сідлові точки"," (градієнт нульовий, але це не мінімум) та ",[5195,7292,7293],{},"плато"," (майже нульовий градієнт на великій області). Модель \"застряє\" на плато, якщо LR занадто малий.",[5191,7296,7297,7300],{},[5195,7298,7299],{},"Розв'язання:"," Періодично збільшувати LR для \"виштовхування\" з плато (Warm Restarts).",[5212,7302,7304,7307],{"icon":4265,"title":7303},"⏱️ Зміна кривизни протягом навчання",[5191,7305,7306],{},"На початку навчання (далеко від мінімуму) ландшафт \"грубий\" — великі LR безпечні. Ближче до мінімуму ландшафт стає \"делікатним\" — потрібні малі LR для точного позиціонування.",[5191,7308,7309,7312,7313,7316],{},[5195,7310,7311],{},"Висновок:"," Оптимальний LR ",[5195,7314,7315],{},"змінюється"," протягом навчання!",[5712,7318],{},[5186,7320,7322],{"id":7321},"основні-типи-learning-rate-schedulers","Основні типи Learning Rate Schedulers",[5191,7324,7325,7326,7329],{},"Тепер, розуміючи проблему фіксованого LR, розглянемо систематичні підходи до його зміни. PyTorch надає клас ",[5244,7327,7328],{},"torch.optim.lr_scheduler"," з готовими реалізаціями популярних стратегій.",[5544,7331,7333],{"id":7332},"_1-steplr-зменшення-кожні-n-епох","1. StepLR — зменшення кожні N епох",[5191,7335,7336,7339,7340,7343,7344,7347],{},[5195,7337,7338],{},"Ідея:"," Зменшувати learning rate на фактор ",[5200,7341],{"tex":7342,":inline":5203},"\\gamma"," кожні ",[5200,7345],{"tex":7346,":inline":5203},"N"," епох.",[5200,7349],{"tex":7350},"\\eta_t = \\eta_0 \\cdot \\gamma^{\\lfloor t \u002F N \\rfloor}",[5191,7352,5733],{},[5625,7354,7355,7361,7366,7371],{},[5628,7356,7357,7360],{},[5200,7358],{"tex":7359,":inline":5203},"\\eta_0"," — початковий learning rate",[5628,7362,7363,7365],{},[5200,7364],{"tex":7342,":inline":5203}," — множник зменшення (зазвичай 0.1 або 0.5)",[5628,7367,7368,7370],{},[5200,7369],{"tex":7346,":inline":5203}," — крок (step_size), кількість епох між зменшеннями",[5628,7372,7373,7375],{},[5200,7374],{"tex":5744,":inline":5203}," — поточна епоха",[5191,7377,7378,5198,7381],{},[5195,7379,7380],{},"Приклад:",[5200,7382],{"tex":7383,":inline":5203},"\\eta_0 = 0.1, \\gamma = 0.1, N = 30",[7125,7385,7386,7399],{},[7128,7387,7388],{},[7131,7389,7390,7393,7396],{},[7134,7391,7392],{"align":7136},"Епоха",[7134,7394,7395],{"align":7136},"Learning Rate",[7134,7397,7398],{"align":7136},"Пояснення",[7151,7400,7401,7411,7425,7439],{},[7131,7402,7403,7406,7408],{},[7156,7404,7405],{"align":7136},"0-29",[7156,7407,6058],{"align":7136},[7156,7409,7410],{"align":7136},"Початковий період",[7131,7412,7413,7416,7419],{},[7156,7414,7415],{"align":7136},"30-59",[7156,7417,7418],{"align":7136},"0.01",[7156,7420,7421,7422],{"align":7136},"Після 30 епох: ",[5200,7423],{"tex":7424,":inline":5203},"0.1 \\times 0.1 = 0.01",[7131,7426,7427,7430,7433],{},[7156,7428,7429],{"align":7136},"60-89",[7156,7431,7432],{"align":7136},"0.001",[7156,7434,7435,7436],{"align":7136},"Після 60 епох: ",[5200,7437],{"tex":7438,":inline":5203},"0.01 \\times 0.1 = 0.001",[7131,7440,7441,7444,7447],{},[7156,7442,7443],{"align":7136},"90+",[7156,7445,7446],{"align":7136},"0.0001",[7156,7448,7449,7450],{"align":7136},"Після 90 епох: ",[5200,7451],{"tex":7452,":inline":5203},"0.001 \\times 0.1 = 0.0001",[5796,7454,7455,7936],{"execution-count":6264},[5237,7456,7458],{"className":5812,"code":7457,"language":5814,"meta":5242,"style":5242},"import torch\nimport torch.optim as optim\nimport matplotlib.pyplot as plt\n\n# Створимо dummy модель та optimizer для демонстрації\nmodel = torch.nn.Linear(10, 1)\noptimizer = optim.SGD(model.parameters(), lr=0.1, momentum=0.9)\n\n# StepLR scheduler\nscheduler = optim.lr_scheduler.StepLR(optimizer, step_size=30, gamma=0.1)\n\n# Симуляція 100 епох\nepochs = 100\nlr_history_step = []\n\nfor epoch in range(epochs):\n    lr_history_step.append(optimizer.param_groups[0]['lr'])\n    \n    # Імітація training step (не важливо для демонстрації scheduler)\n    optimizer.step()\n    \n    # Оновлення LR\n    scheduler.step()\n\n# Візуалізація\nplt.figure(figsize=(12, 5))\nplt.plot(lr_history_step, linewidth=2.5, color='#3b82f6', label='StepLR')\nplt.xlabel('Epoch', fontsize=12)\nplt.ylabel('Learning Rate', fontsize=12)\nplt.title('StepLR Scheduler (step_size=30, gamma=0.1)', fontsize=14, fontweight='bold')\nplt.yscale('log')  # Логарифмічна шкала для кращої візуалізації\nplt.grid(alpha=0.3)\nplt.legend(fontsize=11)\nplt.tight_layout()\nplt.show()\n\nprint(\"📊 StepLR:\")\nprint(f\"├─ Епохи 0-29:   LR = {lr_history_step[0]:.4f}\")\nprint(f\"├─ Епохи 30-59:  LR = {lr_history_step[30]:.4f}\")\nprint(f\"├─ Епохи 60-89:  LR = {lr_history_step[60]:.4f}\")\nprint(f\"└─ Епохи 90-99:  LR = {lr_history_step[90]:.4f}\")\n",[5244,7459,7460,7467,7479,7489,7493,7498,7511,7534,7538,7543,7567,7571,7576,7584,7589,7593,7607,7622,7626,7631,7636,7640,7645,7650,7654,7658,7675,7705,7723,7741,7767,7781,7794,7808,7812,7816,7820,7831,7859,7884,7910],{"__ignoreMap":5242},[5247,7461,7462,7464],{"class":5249,"line":5250},[5247,7463,5822],{"class":5821},[5247,7465,7466],{"class":5825}," torch\n",[5247,7468,7469,7471,7474,7476],{"class":5249,"line":5256},[5247,7470,5822],{"class":5821},[5247,7472,7473],{"class":5825}," torch.optim ",[5247,7475,5829],{"class":5821},[5247,7477,7478],{"class":5825}," optim\n",[5247,7480,7481,7483,7485,7487],{"class":5249,"line":5262},[5247,7482,5822],{"class":5821},[5247,7484,5839],{"class":5825},[5247,7486,5829],{"class":5821},[5247,7488,5844],{"class":5825},[5247,7490,7491],{"class":5249,"line":5268},[5247,7492,5278],{"emptyLinePlaceholder":5277},[5247,7494,7495],{"class":5249,"line":5274},[5247,7496,7497],{"class":5853},"# Створимо dummy модель та optimizer для демонстрації\n",[5247,7499,7500,7503,7505,7507,7509],{"class":5249,"line":5281},[5247,7501,7502],{"class":5825},"model = torch.nn.Linear(",[5247,7504,6555],{"class":5885},[5247,7506,5948],{"class":5825},[5247,7508,5808],{"class":5885},[5247,7510,5924],{"class":5825},[5247,7512,7513,7516,7518,7520,7522,7524,7527,7529,7532],{"class":5249,"line":5287},[5247,7514,7515],{"class":5825},"optimizer = optim.SGD(model.parameters(), ",[5247,7517,5951],{"class":5870},[5247,7519,6055],{"class":5825},[5247,7521,6058],{"class":5885},[5247,7523,5948],{"class":5825},[5247,7525,7526],{"class":5870},"momentum",[5247,7528,6055],{"class":5825},[5247,7530,7531],{"class":5885},"0.9",[5247,7533,5924],{"class":5825},[5247,7535,7536],{"class":5249,"line":5293},[5247,7537,5278],{"emptyLinePlaceholder":5277},[5247,7539,7540],{"class":5249,"line":5299},[5247,7541,7542],{"class":5853},"# StepLR scheduler\n",[5247,7544,7545,7548,7551,7553,7556,7558,7561,7563,7565],{"class":5249,"line":5304},[5247,7546,7547],{"class":5825},"scheduler = optim.lr_scheduler.StepLR(optimizer, ",[5247,7549,7550],{"class":5870},"step_size",[5247,7552,6055],{"class":5825},[5247,7554,7555],{"class":5885},"30",[5247,7557,5948],{"class":5825},[5247,7559,7560],{"class":5870},"gamma",[5247,7562,6055],{"class":5825},[5247,7564,6058],{"class":5885},[5247,7566,5924],{"class":5825},[5247,7568,7569],{"class":5249,"line":5310},[5247,7570,5278],{"emptyLinePlaceholder":5277},[5247,7572,7573],{"class":5249,"line":5316},[5247,7574,7575],{"class":5853},"# Симуляція 100 епох\n",[5247,7577,7578,7581],{"class":5249,"line":5322},[5247,7579,7580],{"class":5825},"epochs = ",[5247,7582,7583],{"class":5885},"100\n",[5247,7585,7586],{"class":5249,"line":5328},[5247,7587,7588],{"class":5825},"lr_history_step = []\n",[5247,7590,7591],{"class":5249,"line":5334},[5247,7592,5278],{"emptyLinePlaceholder":5277},[5247,7594,7595,7597,7600,7602,7604],{"class":5249,"line":5340},[5247,7596,6281],{"class":5821},[5247,7598,7599],{"class":5825}," epoch ",[5247,7601,5984],{"class":5821},[5247,7603,5987],{"class":5863},[5247,7605,7606],{"class":5825},"(epochs):\n",[5247,7608,7609,7612,7614,7617,7620],{"class":5249,"line":5346},[5247,7610,7611],{"class":5825},"    lr_history_step.append(optimizer.param_groups[",[5247,7613,6216],{"class":5885},[5247,7615,7616],{"class":5825},"][",[5247,7618,7619],{"class":6204},"'lr'",[5247,7621,6267],{"class":5825},[5247,7623,7624],{"class":5249,"line":5352},[5247,7625,5973],{"class":5825},[5247,7627,7628],{"class":5249,"line":5358},[5247,7629,7630],{"class":5853},"    # Імітація training step (не важливо для демонстрації scheduler)\n",[5247,7632,7633],{"class":5249,"line":5364},[5247,7634,7635],{"class":5825},"    optimizer.step()\n",[5247,7637,7638],{"class":5249,"line":5369},[5247,7639,5973],{"class":5825},[5247,7641,7642],{"class":5249,"line":5375},[5247,7643,7644],{"class":5853},"    # Оновлення LR\n",[5247,7646,7647],{"class":5249,"line":5380},[5247,7648,7649],{"class":5825},"    scheduler.step()\n",[5247,7651,7652],{"class":5249,"line":5386},[5247,7653,5278],{"emptyLinePlaceholder":5277},[5247,7655,7656],{"class":5249,"line":5392},[5247,7657,6120],{"class":5853},[5247,7659,7660,7663,7665,7667,7669,7671,7673],{"class":5249,"line":5398},[5247,7661,7662],{"class":5825},"plt.figure(",[5247,7664,6136],{"class":5870},[5247,7666,6139],{"class":5825},[5247,7668,6500],{"class":5885},[5247,7670,5948],{"class":5825},[5247,7672,6147],{"class":5885},[5247,7674,6150],{"class":5825},[5247,7676,7677,7680,7682,7684,7686,7688,7690,7692,7694,7696,7698,7700,7703],{"class":5249,"line":5404},[5247,7678,7679],{"class":5825},"plt.plot(lr_history_step, ",[5247,7681,6307],{"class":5870},[5247,7683,6055],{"class":5825},[5247,7685,6428],{"class":5885},[5247,7687,5948],{"class":5825},[5247,7689,6418],{"class":5870},[5247,7691,6055],{"class":5825},[5247,7693,6210],{"class":6204},[5247,7695,5948],{"class":5825},[5247,7697,6327],{"class":5870},[5247,7699,6055],{"class":5825},[5247,7701,7702],{"class":6204},"'StepLR'",[5247,7704,5924],{"class":5825},[5247,7706,7707,7710,7713,7715,7717,7719,7721],{"class":5249,"line":5409},[5247,7708,7709],{"class":5825},"plt.xlabel(",[5247,7711,7712],{"class":6204},"'Epoch'",[5247,7714,5948],{"class":5825},[5247,7716,6653],{"class":5870},[5247,7718,6055],{"class":5825},[5247,7720,6500],{"class":5885},[5247,7722,5924],{"class":5825},[5247,7724,7725,7728,7731,7733,7735,7737,7739],{"class":5249,"line":5414},[5247,7726,7727],{"class":5825},"plt.ylabel(",[5247,7729,7730],{"class":6204},"'Learning Rate'",[5247,7732,5948],{"class":5825},[5247,7734,6653],{"class":5870},[5247,7736,6055],{"class":5825},[5247,7738,6500],{"class":5885},[5247,7740,5924],{"class":5825},[5247,7742,7743,7746,7749,7751,7753,7755,7757,7759,7761,7763,7765],{"class":5249,"line":5419},[5247,7744,7745],{"class":5825},"plt.title(",[5247,7747,7748],{"class":6204},"'StepLR Scheduler (step_size=30, gamma=0.1)'",[5247,7750,5948],{"class":5825},[5247,7752,6653],{"class":5870},[5247,7754,6055],{"class":5825},[5247,7756,6565],{"class":5885},[5247,7758,5948],{"class":5825},[5247,7760,6721],{"class":5870},[5247,7762,6055],{"class":5825},[5247,7764,6726],{"class":6204},[5247,7766,5924],{"class":5825},[5247,7768,7769,7772,7775,7778],{"class":5249,"line":5425},[5247,7770,7771],{"class":5825},"plt.yscale(",[5247,7773,7774],{"class":6204},"'log'",[5247,7776,7777],{"class":5825},")  ",[5247,7779,7780],{"class":5853},"# Логарифмічна шкала для кращої візуалізації\n",[5247,7782,7783,7786,7788,7790,7792],{"class":5249,"line":5430},[5247,7784,7785],{"class":5825},"plt.grid(",[5247,7787,6317],{"class":5870},[5247,7789,6055],{"class":5825},[5247,7791,6322],{"class":5885},[5247,7793,5924],{"class":5825},[5247,7795,7796,7799,7801,7803,7806],{"class":5249,"line":5436},[5247,7797,7798],{"class":5825},"plt.legend(",[5247,7800,6653],{"class":5870},[5247,7802,6055],{"class":5825},[5247,7804,7805],{"class":5885},"11",[5247,7807,5924],{"class":5825},[5247,7809,7810],{"class":5249,"line":5442},[5247,7811,6782],{"class":5825},[5247,7813,7814],{"class":5249,"line":5448},[5247,7815,6788],{"class":5825},[5247,7817,7818],{"class":5249,"line":5454},[5247,7819,5278],{"emptyLinePlaceholder":5277},[5247,7821,7822,7824,7826,7829],{"class":5249,"line":5460},[5247,7823,6805],{"class":5863},[5247,7825,5867],{"class":5825},[5247,7827,7828],{"class":6204},"\"📊 StepLR:\"",[5247,7830,5924],{"class":5825},[5247,7832,7833,7835,7837,7839,7842,7844,7847,7849,7852,7855,7857],{"class":5249,"line":5466},[5247,7834,6805],{"class":5863},[5247,7836,5867],{"class":5825},[5247,7838,6601],{"class":5859},[5247,7840,7841],{"class":6204},"\"├─ Епохи 0-29:   LR = ",[5247,7843,6607],{"class":5859},[5247,7845,7846],{"class":5825},"lr_history_step[",[5247,7848,6216],{"class":5885},[5247,7850,7851],{"class":5825},"]",[5247,7853,7854],{"class":5859},":.4f}",[5247,7856,6817],{"class":6204},[5247,7858,5924],{"class":5825},[5247,7860,7861,7863,7865,7867,7870,7872,7874,7876,7878,7880,7882],{"class":5249,"line":5472},[5247,7862,6805],{"class":5863},[5247,7864,5867],{"class":5825},[5247,7866,6601],{"class":5859},[5247,7868,7869],{"class":6204},"\"├─ Епохи 30-59:  LR = ",[5247,7871,6607],{"class":5859},[5247,7873,7846],{"class":5825},[5247,7875,7555],{"class":5885},[5247,7877,7851],{"class":5825},[5247,7879,7854],{"class":5859},[5247,7881,6817],{"class":6204},[5247,7883,5924],{"class":5825},[5247,7885,7886,7888,7890,7892,7895,7897,7899,7902,7904,7906,7908],{"class":5249,"line":5477},[5247,7887,6805],{"class":5863},[5247,7889,5867],{"class":5825},[5247,7891,6601],{"class":5859},[5247,7893,7894],{"class":6204},"\"├─ Епохи 60-89:  LR = ",[5247,7896,6607],{"class":5859},[5247,7898,7846],{"class":5825},[5247,7900,7901],{"class":5885},"60",[5247,7903,7851],{"class":5825},[5247,7905,7854],{"class":5859},[5247,7907,6817],{"class":6204},[5247,7909,5924],{"class":5825},[5247,7911,7912,7914,7916,7918,7921,7923,7925,7928,7930,7932,7934],{"class":5249,"line":5482},[5247,7913,6805],{"class":5863},[5247,7915,5867],{"class":5825},[5247,7917,6601],{"class":5859},[5247,7919,7920],{"class":6204},"\"└─ Епохи 90-99:  LR = ",[5247,7922,6607],{"class":5859},[5247,7924,7846],{"class":5825},[5247,7926,7927],{"class":5885},"90",[5247,7929,7851],{"class":5825},[5247,7931,7854],{"class":5859},[5247,7933,6817],{"class":6204},[5247,7935,5924],{"class":5825},[7107,7937,7938,7945,7950],{"v-slot:output":5242},[5191,7939,7940],{},[7112,7941],{"alt":7942,"className":7943,"src":7944},"StepLR: різкі падіння LR кожні 30 епох",[7116],"\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling\u002F02.png",[5191,7946,7120,7947],{},[5195,7948,7949],{},"StepLR:",[5625,7951,7952,7955,7958,7961],{},[5628,7953,7954],{},"Епохи 0-29:   LR = 0.1000",[5628,7956,7957],{},"Епохи 30-59:  LR = 0.0100",[5628,7959,7960],{},"Епохи 60-89:  LR = 0.0010",[5628,7962,7963],{},"Епохи 90-99:  LR = 0.0001",[5191,7965,7966],{},[5195,7967,7968],{},"Переваги:",[5625,7970,7971,7974,7977],{},[5628,7972,7973],{},"✅ Простота реалізації та налаштування",[5628,7975,7976],{},"✅ Передбачуваність (знаєте, коли LR зміниться)",[5628,7978,7979],{},"✅ Добре працює для більшості задач",[5191,7981,7982],{},[5195,7983,7984],{},"Недоліки:",[5625,7986,7987,7990,7993],{},[5628,7988,7989],{},"❌ Різкі стрибки можуть \"шокувати\" модель",[5628,7991,7992],{},"❌ Потрібно вручну обирати step_size (гіперпараметр)",[5628,7994,7995],{},"❌ Фіксовані епохи можуть не співпадати з оптимальними моментами",[5191,7997,7998,8001],{},[5195,7999,8000],{},"Коли використовувати:"," За замовчуванням для більшості CNN на фіксованій кількості епох (наприклад, 100-200 епох).",[5712,8003],{},[5544,8005,8007],{"id":8006},"_2-multisteplr-зменшення-у-конкретні-епохи","2. MultiStepLR — зменшення у конкретні епохи",[5191,8009,8010,8012],{},[5195,8011,7338],{}," Розширення StepLR — зменшуємо LR у заздалегідь визначені епохи (milestones).",[5200,8014],{"tex":8015},"\\eta_t = \\eta_0 \\cdot \\gamma^{\\sum_{i} \\mathbb{1}(t \\geq m_i)}",[5191,8017,8018,8019,8022],{},"Де ",[5200,8020],{"tex":8021,":inline":5203},"m_i"," — milestone епохи.",[5796,8024,8025,8450],{"execution-count":5886},[5237,8026,8028],{"className":5812,"code":8027,"language":5814,"meta":5242,"style":5242},"# MultiStepLR scheduler\noptimizer = optim.SGD(model.parameters(), lr=0.1, momentum=0.9)\nscheduler = optim.lr_scheduler.MultiStepLR(optimizer, milestones=[30, 60, 90], gamma=0.1)\n\nlr_history_multistep = []\nfor epoch in range(epochs):\n    lr_history_multistep.append(optimizer.param_groups[0]['lr'])\n    optimizer.step()\n    scheduler.step()\n\n# Візуалізація\nplt.figure(figsize=(12, 5))\nplt.plot(lr_history_multistep, linewidth=2.5, color='#8b5cf6', label='MultiStepLR')\n\n# Вертикальні лінії на milestones\nfor milestone in [30, 60, 90]:\n    plt.axvline(x=milestone, color='red', linestyle='--', alpha=0.5, linewidth=1.5)\n    plt.text(milestone, 0.15, f'Milestone\\n{milestone}', ha='center', fontsize=9, \n             bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.5))\n\nplt.xlabel('Epoch', fontsize=12)\nplt.ylabel('Learning Rate', fontsize=12)\nplt.title('MultiStepLR Scheduler (milestones=[30, 60, 90], gamma=0.1)', fontsize=14, fontweight='bold')\nplt.yscale('log')\nplt.grid(alpha=0.3)\nplt.legend(fontsize=11)\nplt.tight_layout()\nplt.show()\n",[5244,8029,8030,8035,8055,8086,8090,8095,8107,8120,8124,8128,8132,8136,8152,8183,8187,8192,8216,8262,8308,8349,8353,8369,8385,8410,8418,8430,8442,8446],{"__ignoreMap":5242},[5247,8031,8032],{"class":5249,"line":5250},[5247,8033,8034],{"class":5853},"# MultiStepLR scheduler\n",[5247,8036,8037,8039,8041,8043,8045,8047,8049,8051,8053],{"class":5249,"line":5256},[5247,8038,7515],{"class":5825},[5247,8040,5951],{"class":5870},[5247,8042,6055],{"class":5825},[5247,8044,6058],{"class":5885},[5247,8046,5948],{"class":5825},[5247,8048,7526],{"class":5870},[5247,8050,6055],{"class":5825},[5247,8052,7531],{"class":5885},[5247,8054,5924],{"class":5825},[5247,8056,8057,8060,8063,8066,8068,8070,8072,8074,8076,8078,8080,8082,8084],{"class":5249,"line":5262},[5247,8058,8059],{"class":5825},"scheduler = optim.lr_scheduler.MultiStepLR(optimizer, ",[5247,8061,8062],{"class":5870},"milestones",[5247,8064,8065],{"class":5825},"=[",[5247,8067,7555],{"class":5885},[5247,8069,5948],{"class":5825},[5247,8071,7901],{"class":5885},[5247,8073,5948],{"class":5825},[5247,8075,7927],{"class":5885},[5247,8077,6488],{"class":5825},[5247,8079,7560],{"class":5870},[5247,8081,6055],{"class":5825},[5247,8083,6058],{"class":5885},[5247,8085,5924],{"class":5825},[5247,8087,8088],{"class":5249,"line":5268},[5247,8089,5278],{"emptyLinePlaceholder":5277},[5247,8091,8092],{"class":5249,"line":5274},[5247,8093,8094],{"class":5825},"lr_history_multistep = []\n",[5247,8096,8097,8099,8101,8103,8105],{"class":5249,"line":5281},[5247,8098,6281],{"class":5821},[5247,8100,7599],{"class":5825},[5247,8102,5984],{"class":5821},[5247,8104,5987],{"class":5863},[5247,8106,7606],{"class":5825},[5247,8108,8109,8112,8114,8116,8118],{"class":5249,"line":5287},[5247,8110,8111],{"class":5825},"    lr_history_multistep.append(optimizer.param_groups[",[5247,8113,6216],{"class":5885},[5247,8115,7616],{"class":5825},[5247,8117,7619],{"class":6204},[5247,8119,6267],{"class":5825},[5247,8121,8122],{"class":5249,"line":5293},[5247,8123,7635],{"class":5825},[5247,8125,8126],{"class":5249,"line":5299},[5247,8127,7649],{"class":5825},[5247,8129,8130],{"class":5249,"line":5304},[5247,8131,5278],{"emptyLinePlaceholder":5277},[5247,8133,8134],{"class":5249,"line":5310},[5247,8135,6120],{"class":5853},[5247,8137,8138,8140,8142,8144,8146,8148,8150],{"class":5249,"line":5316},[5247,8139,7662],{"class":5825},[5247,8141,6136],{"class":5870},[5247,8143,6139],{"class":5825},[5247,8145,6500],{"class":5885},[5247,8147,5948],{"class":5825},[5247,8149,6147],{"class":5885},[5247,8151,6150],{"class":5825},[5247,8153,8154,8157,8159,8161,8163,8165,8167,8169,8172,8174,8176,8178,8181],{"class":5249,"line":5322},[5247,8155,8156],{"class":5825},"plt.plot(lr_history_multistep, ",[5247,8158,6307],{"class":5870},[5247,8160,6055],{"class":5825},[5247,8162,6428],{"class":5885},[5247,8164,5948],{"class":5825},[5247,8166,6418],{"class":5870},[5247,8168,6055],{"class":5825},[5247,8170,8171],{"class":6204},"'#8b5cf6'",[5247,8173,5948],{"class":5825},[5247,8175,6327],{"class":5870},[5247,8177,6055],{"class":5825},[5247,8179,8180],{"class":6204},"'MultiStepLR'",[5247,8182,5924],{"class":5825},[5247,8184,8185],{"class":5249,"line":5328},[5247,8186,5278],{"emptyLinePlaceholder":5277},[5247,8188,8189],{"class":5249,"line":5334},[5247,8190,8191],{"class":5853},"# Вертикальні лінії на milestones\n",[5247,8193,8194,8196,8199,8201,8203,8205,8207,8209,8211,8213],{"class":5249,"line":5340},[5247,8195,6281],{"class":5821},[5247,8197,8198],{"class":5825}," milestone ",[5247,8200,5984],{"class":5821},[5247,8202,6544],{"class":5825},[5247,8204,7555],{"class":5885},[5247,8206,5948],{"class":5825},[5247,8208,7901],{"class":5885},[5247,8210,5948],{"class":5825},[5247,8212,7927],{"class":5885},[5247,8214,8215],{"class":5825},"]:\n",[5247,8217,8218,8221,8224,8227,8229,8231,8234,8236,8239,8241,8244,8246,8248,8250,8252,8254,8256,8258,8260],{"class":5249,"line":5346},[5247,8219,8220],{"class":5825},"    plt.axvline(",[5247,8222,8223],{"class":5870},"x",[5247,8225,8226],{"class":5825},"=milestone, ",[5247,8228,6418],{"class":5870},[5247,8230,6055],{"class":5825},[5247,8232,8233],{"class":6204},"'red'",[5247,8235,5948],{"class":5825},[5247,8237,8238],{"class":5870},"linestyle",[5247,8240,6055],{"class":5825},[5247,8242,8243],{"class":6204},"'--'",[5247,8245,5948],{"class":5825},[5247,8247,6317],{"class":5870},[5247,8249,6055],{"class":5825},[5247,8251,6080],{"class":5885},[5247,8253,5948],{"class":5825},[5247,8255,6307],{"class":5870},[5247,8257,6055],{"class":5825},[5247,8259,6312],{"class":5885},[5247,8261,5924],{"class":5825},[5247,8263,8264,8267,8270,8272,8274,8277,8279,8281,8284,8286,8288,8290,8293,8295,8298,8300,8302,8304,8306],{"class":5249,"line":5352},[5247,8265,8266],{"class":5825},"    plt.text(milestone, ",[5247,8268,8269],{"class":5885},"0.15",[5247,8271,5948],{"class":5825},[5247,8273,6601],{"class":5859},[5247,8275,8276],{"class":6204},"'Milestone",[5247,8278,6814],{"class":6813},[5247,8280,6607],{"class":5859},[5247,8282,8283],{"class":5825},"milestone",[5247,8285,6613],{"class":5859},[5247,8287,6604],{"class":6204},[5247,8289,5948],{"class":5825},[5247,8291,8292],{"class":5870},"ha",[5247,8294,6055],{"class":5825},[5247,8296,8297],{"class":6204},"'center'",[5247,8299,5948],{"class":5825},[5247,8301,6653],{"class":5870},[5247,8303,6055],{"class":5825},[5247,8305,6658],{"class":5885},[5247,8307,6431],{"class":5825},[5247,8309,8310,8313,8315,8319,8321,8324,8326,8329,8331,8334,8336,8339,8341,8343,8345,8347],{"class":5249,"line":5358},[5247,8311,8312],{"class":5870},"             bbox",[5247,8314,6055],{"class":5825},[5247,8316,8318],{"class":8317},"sN1BT","dict",[5247,8320,5867],{"class":5825},[5247,8322,8323],{"class":5870},"boxstyle",[5247,8325,6055],{"class":5825},[5247,8327,8328],{"class":6204},"'round'",[5247,8330,5948],{"class":5825},[5247,8332,8333],{"class":5870},"facecolor",[5247,8335,6055],{"class":5825},[5247,8337,8338],{"class":6204},"'wheat'",[5247,8340,5948],{"class":5825},[5247,8342,6317],{"class":5870},[5247,8344,6055],{"class":5825},[5247,8346,6080],{"class":5885},[5247,8348,6150],{"class":5825},[5247,8350,8351],{"class":5249,"line":5364},[5247,8352,5278],{"emptyLinePlaceholder":5277},[5247,8354,8355,8357,8359,8361,8363,8365,8367],{"class":5249,"line":5369},[5247,8356,7709],{"class":5825},[5247,8358,7712],{"class":6204},[5247,8360,5948],{"class":5825},[5247,8362,6653],{"class":5870},[5247,8364,6055],{"class":5825},[5247,8366,6500],{"class":5885},[5247,8368,5924],{"class":5825},[5247,8370,8371,8373,8375,8377,8379,8381,8383],{"class":5249,"line":5375},[5247,8372,7727],{"class":5825},[5247,8374,7730],{"class":6204},[5247,8376,5948],{"class":5825},[5247,8378,6653],{"class":5870},[5247,8380,6055],{"class":5825},[5247,8382,6500],{"class":5885},[5247,8384,5924],{"class":5825},[5247,8386,8387,8389,8392,8394,8396,8398,8400,8402,8404,8406,8408],{"class":5249,"line":5380},[5247,8388,7745],{"class":5825},[5247,8390,8391],{"class":6204},"'MultiStepLR Scheduler (milestones=[30, 60, 90], gamma=0.1)'",[5247,8393,5948],{"class":5825},[5247,8395,6653],{"class":5870},[5247,8397,6055],{"class":5825},[5247,8399,6565],{"class":5885},[5247,8401,5948],{"class":5825},[5247,8403,6721],{"class":5870},[5247,8405,6055],{"class":5825},[5247,8407,6726],{"class":6204},[5247,8409,5924],{"class":5825},[5247,8411,8412,8414,8416],{"class":5249,"line":5386},[5247,8413,7771],{"class":5825},[5247,8415,7774],{"class":6204},[5247,8417,5924],{"class":5825},[5247,8419,8420,8422,8424,8426,8428],{"class":5249,"line":5392},[5247,8421,7785],{"class":5825},[5247,8423,6317],{"class":5870},[5247,8425,6055],{"class":5825},[5247,8427,6322],{"class":5885},[5247,8429,5924],{"class":5825},[5247,8431,8432,8434,8436,8438,8440],{"class":5249,"line":5398},[5247,8433,7798],{"class":5825},[5247,8435,6653],{"class":5870},[5247,8437,6055],{"class":5825},[5247,8439,7805],{"class":5885},[5247,8441,5924],{"class":5825},[5247,8443,8444],{"class":5249,"line":5404},[5247,8445,6782],{"class":5825},[5247,8447,8448],{"class":5249,"line":5409},[5247,8449,6788],{"class":5825},[7107,8451,8452],{"v-slot:output":5242},[7112,8453],{"alt":8454,"className":8455,"src":8456},"MultiStepLR: зменшення у конкретні епохи (30, 60, 90)",[7116],"\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling\u002F03.png",[5191,8458,8459],{},[5195,8460,7968],{},[5625,8462,8463,8466],{},[5628,8464,8465],{},"✅ Повний контроль над моментами зміни LR",[5628,8467,8468],{},"✅ Можна адаптувати під конкретний графік навчання",[5191,8470,8471,8473],{},[5195,8472,8000],{}," Коли ви з досвіду знаєте, на яких епохах модель \"застряє\" (наприклад, з попередніх експериментів).",[5712,8475],{},[5544,8477,8479],{"id":8478},"_3-exponentiallr-експоненціальне-зменшення","3. ExponentialLR — експоненціальне зменшення",[5191,8481,8482,8484,8485,5198,8487,8490],{},[5195,8483,7338],{}," Зменшувати LR на фактор ",[5200,8486],{"tex":7342,":inline":5203},[5195,8488,8489],{},"кожну епоху"," (а не кожні N епох).",[5200,8492],{"tex":8493},"\\eta_t = \\eta_0 \\cdot \\gamma^t",[5191,8495,8496,5198,8498],{},[5195,8497,7380],{},[5200,8499],{"tex":8500,":inline":5203},"\\eta_0 = 0.1, \\gamma = 0.95",[5796,8502,8503,8889],{"execution-count":6518},[5237,8504,8506],{"className":5812,"code":8505,"language":5814,"meta":5242,"style":5242},"# ExponentialLR scheduler\noptimizer = optim.SGD(model.parameters(), lr=0.1, momentum=0.9)\nscheduler = optim.lr_scheduler.ExponentialLR(optimizer, gamma=0.95)\n\nlr_history_exp = []\nfor epoch in range(epochs):\n    lr_history_exp.append(optimizer.param_groups[0]['lr'])\n    optimizer.step()\n    scheduler.step()\n\n# Візуалізація\nplt.figure(figsize=(12, 5))\nplt.plot(lr_history_exp, linewidth=2.5, color='#f59e0b', label='ExponentialLR (gamma=0.95)')\nplt.xlabel('Epoch', fontsize=12)\nplt.ylabel('Learning Rate', fontsize=12)\nplt.title('ExponentialLR Scheduler — плавне зменшення', fontsize=14, fontweight='bold')\nplt.yscale('log')\nplt.grid(alpha=0.3)\nplt.legend(fontsize=11)\nplt.tight_layout()\nplt.show()\n\nprint(f\"📊 ExponentialLR (gamma=0.95):\")\nprint(f\"├─ Епоха 0:   LR = {lr_history_exp[0]:.6f}\")\nprint(f\"├─ Епоха 25:  LR = {lr_history_exp[25]:.6f}\")\nprint(f\"├─ Епоха 50:  LR = {lr_history_exp[50]:.6f}\")\nprint(f\"├─ Епоха 75:  LR = {lr_history_exp[75]:.6f}\")\nprint(f\"└─ Епоха 99:  LR = {lr_history_exp[99]:.6f}\")\n",[5244,8507,8508,8513,8533,8547,8551,8556,8568,8581,8585,8589,8593,8597,8613,8644,8660,8676,8701,8709,8721,8733,8737,8741,8745,8758,8785,8811,8837,8863],{"__ignoreMap":5242},[5247,8509,8510],{"class":5249,"line":5250},[5247,8511,8512],{"class":5853},"# ExponentialLR scheduler\n",[5247,8514,8515,8517,8519,8521,8523,8525,8527,8529,8531],{"class":5249,"line":5256},[5247,8516,7515],{"class":5825},[5247,8518,5951],{"class":5870},[5247,8520,6055],{"class":5825},[5247,8522,6058],{"class":5885},[5247,8524,5948],{"class":5825},[5247,8526,7526],{"class":5870},[5247,8528,6055],{"class":5825},[5247,8530,7531],{"class":5885},[5247,8532,5924],{"class":5825},[5247,8534,8535,8538,8540,8542,8545],{"class":5249,"line":5262},[5247,8536,8537],{"class":5825},"scheduler = optim.lr_scheduler.ExponentialLR(optimizer, ",[5247,8539,7560],{"class":5870},[5247,8541,6055],{"class":5825},[5247,8543,8544],{"class":5885},"0.95",[5247,8546,5924],{"class":5825},[5247,8548,8549],{"class":5249,"line":5268},[5247,8550,5278],{"emptyLinePlaceholder":5277},[5247,8552,8553],{"class":5249,"line":5274},[5247,8554,8555],{"class":5825},"lr_history_exp = []\n",[5247,8557,8558,8560,8562,8564,8566],{"class":5249,"line":5281},[5247,8559,6281],{"class":5821},[5247,8561,7599],{"class":5825},[5247,8563,5984],{"class":5821},[5247,8565,5987],{"class":5863},[5247,8567,7606],{"class":5825},[5247,8569,8570,8573,8575,8577,8579],{"class":5249,"line":5287},[5247,8571,8572],{"class":5825},"    lr_history_exp.append(optimizer.param_groups[",[5247,8574,6216],{"class":5885},[5247,8576,7616],{"class":5825},[5247,8578,7619],{"class":6204},[5247,8580,6267],{"class":5825},[5247,8582,8583],{"class":5249,"line":5293},[5247,8584,7635],{"class":5825},[5247,8586,8587],{"class":5249,"line":5299},[5247,8588,7649],{"class":5825},[5247,8590,8591],{"class":5249,"line":5304},[5247,8592,5278],{"emptyLinePlaceholder":5277},[5247,8594,8595],{"class":5249,"line":5310},[5247,8596,6120],{"class":5853},[5247,8598,8599,8601,8603,8605,8607,8609,8611],{"class":5249,"line":5316},[5247,8600,7662],{"class":5825},[5247,8602,6136],{"class":5870},[5247,8604,6139],{"class":5825},[5247,8606,6500],{"class":5885},[5247,8608,5948],{"class":5825},[5247,8610,6147],{"class":5885},[5247,8612,6150],{"class":5825},[5247,8614,8615,8618,8620,8622,8624,8626,8628,8630,8633,8635,8637,8639,8642],{"class":5249,"line":5322},[5247,8616,8617],{"class":5825},"plt.plot(lr_history_exp, ",[5247,8619,6307],{"class":5870},[5247,8621,6055],{"class":5825},[5247,8623,6428],{"class":5885},[5247,8625,5948],{"class":5825},[5247,8627,6418],{"class":5870},[5247,8629,6055],{"class":5825},[5247,8631,8632],{"class":6204},"'#f59e0b'",[5247,8634,5948],{"class":5825},[5247,8636,6327],{"class":5870},[5247,8638,6055],{"class":5825},[5247,8640,8641],{"class":6204},"'ExponentialLR (gamma=0.95)'",[5247,8643,5924],{"class":5825},[5247,8645,8646,8648,8650,8652,8654,8656,8658],{"class":5249,"line":5328},[5247,8647,7709],{"class":5825},[5247,8649,7712],{"class":6204},[5247,8651,5948],{"class":5825},[5247,8653,6653],{"class":5870},[5247,8655,6055],{"class":5825},[5247,8657,6500],{"class":5885},[5247,8659,5924],{"class":5825},[5247,8661,8662,8664,8666,8668,8670,8672,8674],{"class":5249,"line":5334},[5247,8663,7727],{"class":5825},[5247,8665,7730],{"class":6204},[5247,8667,5948],{"class":5825},[5247,8669,6653],{"class":5870},[5247,8671,6055],{"class":5825},[5247,8673,6500],{"class":5885},[5247,8675,5924],{"class":5825},[5247,8677,8678,8680,8683,8685,8687,8689,8691,8693,8695,8697,8699],{"class":5249,"line":5340},[5247,8679,7745],{"class":5825},[5247,8681,8682],{"class":6204},"'ExponentialLR Scheduler — плавне зменшення'",[5247,8684,5948],{"class":5825},[5247,8686,6653],{"class":5870},[5247,8688,6055],{"class":5825},[5247,8690,6565],{"class":5885},[5247,8692,5948],{"class":5825},[5247,8694,6721],{"class":5870},[5247,8696,6055],{"class":5825},[5247,8698,6726],{"class":6204},[5247,8700,5924],{"class":5825},[5247,8702,8703,8705,8707],{"class":5249,"line":5346},[5247,8704,7771],{"class":5825},[5247,8706,7774],{"class":6204},[5247,8708,5924],{"class":5825},[5247,8710,8711,8713,8715,8717,8719],{"class":5249,"line":5352},[5247,8712,7785],{"class":5825},[5247,8714,6317],{"class":5870},[5247,8716,6055],{"class":5825},[5247,8718,6322],{"class":5885},[5247,8720,5924],{"class":5825},[5247,8722,8723,8725,8727,8729,8731],{"class":5249,"line":5358},[5247,8724,7798],{"class":5825},[5247,8726,6653],{"class":5870},[5247,8728,6055],{"class":5825},[5247,8730,7805],{"class":5885},[5247,8732,5924],{"class":5825},[5247,8734,8735],{"class":5249,"line":5364},[5247,8736,6782],{"class":5825},[5247,8738,8739],{"class":5249,"line":5369},[5247,8740,6788],{"class":5825},[5247,8742,8743],{"class":5249,"line":5375},[5247,8744,5278],{"emptyLinePlaceholder":5277},[5247,8746,8747,8749,8751,8753,8756],{"class":5249,"line":5380},[5247,8748,6805],{"class":5863},[5247,8750,5867],{"class":5825},[5247,8752,6601],{"class":5859},[5247,8754,8755],{"class":6204},"\"📊 ExponentialLR (gamma=0.95):\"",[5247,8757,5924],{"class":5825},[5247,8759,8760,8762,8764,8766,8769,8771,8774,8776,8778,8781,8783],{"class":5249,"line":5386},[5247,8761,6805],{"class":5863},[5247,8763,5867],{"class":5825},[5247,8765,6601],{"class":5859},[5247,8767,8768],{"class":6204},"\"├─ Епоха 0:   LR = ",[5247,8770,6607],{"class":5859},[5247,8772,8773],{"class":5825},"lr_history_exp[",[5247,8775,6216],{"class":5885},[5247,8777,7851],{"class":5825},[5247,8779,8780],{"class":5859},":.6f}",[5247,8782,6817],{"class":6204},[5247,8784,5924],{"class":5825},[5247,8786,8787,8789,8791,8793,8796,8798,8800,8803,8805,8807,8809],{"class":5249,"line":5392},[5247,8788,6805],{"class":5863},[5247,8790,5867],{"class":5825},[5247,8792,6601],{"class":5859},[5247,8794,8795],{"class":6204},"\"├─ Епоха 25:  LR = ",[5247,8797,6607],{"class":5859},[5247,8799,8773],{"class":5825},[5247,8801,8802],{"class":5885},"25",[5247,8804,7851],{"class":5825},[5247,8806,8780],{"class":5859},[5247,8808,6817],{"class":6204},[5247,8810,5924],{"class":5825},[5247,8812,8813,8815,8817,8819,8822,8824,8826,8829,8831,8833,8835],{"class":5249,"line":5398},[5247,8814,6805],{"class":5863},[5247,8816,5867],{"class":5825},[5247,8818,6601],{"class":5859},[5247,8820,8821],{"class":6204},"\"├─ Епоха 50:  LR = ",[5247,8823,6607],{"class":5859},[5247,8825,8773],{"class":5825},[5247,8827,8828],{"class":5885},"50",[5247,8830,7851],{"class":5825},[5247,8832,8780],{"class":5859},[5247,8834,6817],{"class":6204},[5247,8836,5924],{"class":5825},[5247,8838,8839,8841,8843,8845,8848,8850,8852,8855,8857,8859,8861],{"class":5249,"line":5404},[5247,8840,6805],{"class":5863},[5247,8842,5867],{"class":5825},[5247,8844,6601],{"class":5859},[5247,8846,8847],{"class":6204},"\"├─ Епоха 75:  LR = ",[5247,8849,6607],{"class":5859},[5247,8851,8773],{"class":5825},[5247,8853,8854],{"class":5885},"75",[5247,8856,7851],{"class":5825},[5247,8858,8780],{"class":5859},[5247,8860,6817],{"class":6204},[5247,8862,5924],{"class":5825},[5247,8864,8865,8867,8869,8871,8874,8876,8878,8881,8883,8885,8887],{"class":5249,"line":5409},[5247,8866,6805],{"class":5863},[5247,8868,5867],{"class":5825},[5247,8870,6601],{"class":5859},[5247,8872,8873],{"class":6204},"\"└─ Епоха 99:  LR = ",[5247,8875,6607],{"class":5859},[5247,8877,8773],{"class":5825},[5247,8879,8880],{"class":5885},"99",[5247,8882,7851],{"class":5825},[5247,8884,8780],{"class":5859},[5247,8886,6817],{"class":6204},[5247,8888,5924],{"class":5825},[7107,8890,8891,8898,8903],{"v-slot:output":5242},[5191,8892,8893],{},[7112,8894],{"alt":8895,"className":8896,"src":8897},"ExponentialLR: гладке експоненціальне зменшення",[7116],"\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling\u002F04.png",[5191,8899,7120,8900],{},[5195,8901,8902],{},"ExponentialLR (gamma=0.95):",[5625,8904,8905,8908,8911,8914,8917],{},[5628,8906,8907],{},"Епоха 0:   LR = 0.100000",[5628,8909,8910],{},"Епоха 25:  LR = 0.027741 (зменшення у ~3.6 рази)",[5628,8912,8913],{},"Епоха 50:  LR = 0.007694 (зменшення у ~13 разів)",[5628,8915,8916],{},"Епоха 75:  LR = 0.002134 (зменшення у ~47 разів)",[5628,8918,8919],{},"Епоха 99:  LR = 0.000592 (зменшення у ~169 разів)",[5191,8921,8922],{},[5195,8923,7968],{},[5625,8925,8926,8929],{},[5628,8927,8928],{},"✅ Плавна зміна без різких стрибків",[5628,8930,8931,8932],{},"✅ Простий єдиний параметр ",[5200,8933],{"tex":7342,":inline":5203},[5191,8935,8936],{},[5195,8937,7984],{},[5625,8939,8940,8946],{},[5628,8941,8942,8943,8945],{},"❌ Важко інтуїтивно підібрати ",[5200,8944],{"tex":7342,":inline":5203}," (0.95? 0.98? 0.99?)",[5628,8947,8948],{},"❌ LR може стати занадто малим на пізніх епохах",[5191,8950,8951,8953],{},[5195,8952,8000],{}," Коли потрібна плавна зміна LR, особливо для довгих тренувань (500+ епох).",[5712,8955],{},[5544,8957,8959],{"id":8958},"_4-cosineannealinglr-косинусоїдальне-зменшення","4. CosineAnnealingLR — косинусоїдальне зменшення",[5191,8961,8962,8964,8965,8968,8969,8972,8973,7347],{},[5195,8963,7338],{}," Зменшувати LR за косинусоїдою від ",[5200,8966],{"tex":8967,":inline":5203},"\\eta_{\\text{max}}"," до ",[5200,8970],{"tex":8971,":inline":5203},"\\eta_{\\text{min}}"," протягом ",[5200,8974],{"tex":8975,":inline":5203},"T_{\\text{max}}",[5200,8977],{"tex":8978},"\\eta_t = \\eta_{\\text{min}} + \\frac{1}{2}(\\eta_{\\text{max}} - \\eta_{\\text{min}})\\left(1 + \\cos\\left(\\frac{t}{T_{\\text{max}}} \\pi\\right)\\right)",[5191,8980,5733],{},[5625,8982,8983,8988,8993],{},[5628,8984,8985,8987],{},[5200,8986],{"tex":8967,":inline":5203}," — початковий LR (0.1)",[5628,8989,8990,8992],{},[5200,8991],{"tex":8971,":inline":5203}," — мінімальний LR (зазвичай 0 або 1e-6)",[5628,8994,8995,8997],{},[5200,8996],{"tex":8975,":inline":5203}," — загальна кількість епох для одного циклу",[5191,8999,9000,9003],{},[5195,9001,9002],{},"Візуальна інтуїція:"," Уявіть половину косинусної хвилі, що плавно спускається від максимуму до мінімуму.",[5796,9005,9006,9510],{"execution-count":6147},[5237,9007,9009],{"className":5812,"code":9008,"language":5814,"meta":5242,"style":5242},"# CosineAnnealingLR scheduler\noptimizer = optim.SGD(model.parameters(), lr=0.1, momentum=0.9)\nscheduler = optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=100, eta_min=1e-6)\n\nlr_history_cosine = []\nfor epoch in range(epochs):\n    lr_history_cosine.append(optimizer.param_groups[0]['lr'])\n    optimizer.step()\n    scheduler.step()\n\n# Візуалізація всіх schedulers разом для порівняння\nfig, axes = plt.subplots(1, 2, figsize=(16, 5))\n\n# Графік 1: CosineAnnealingLR\nax = axes[0]\nax.plot(lr_history_cosine, linewidth=2.5, color='#22c55e', label='CosineAnnealingLR')\nax.set_xlabel('Epoch', fontsize=12)\nax.set_ylabel('Learning Rate', fontsize=12)\nax.set_title('CosineAnnealingLR — плавна косинусоїда', fontsize=14, fontweight='bold')\nax.grid(alpha=0.3)\nax.legend(fontsize=11)\n\n# Графік 2: Порівняння всіх schedulers\nax = axes[1]\nax.plot(lr_history_step, linewidth=2, label='StepLR', alpha=0.8)\nax.plot(lr_history_multistep, linewidth=2, label='MultiStepLR', alpha=0.8)\nax.plot(lr_history_exp, linewidth=2, label='ExponentialLR', alpha=0.8)\nax.plot(lr_history_cosine, linewidth=2, label='CosineAnnealingLR', alpha=0.8)\n\nax.set_xlabel('Epoch', fontsize=12)\nax.set_ylabel('Learning Rate', fontsize=12)\nax.set_title('Порівняння всіх schedulers', fontsize=14, fontweight='bold')\nax.set_yscale('log')\nax.grid(alpha=0.3)\nax.legend(fontsize=10)\n\nplt.tight_layout()\nplt.show()\n",[5244,9010,9011,9016,9036,9061,9065,9070,9082,9095,9099,9103,9107,9112,9137,9141,9146,9155,9185,9202,9219,9245,9258,9271,9275,9280,9288,9317,9346,9376,9404,9408,9424,9440,9465,9474,9486,9498,9502,9506],{"__ignoreMap":5242},[5247,9012,9013],{"class":5249,"line":5250},[5247,9014,9015],{"class":5853},"# CosineAnnealingLR scheduler\n",[5247,9017,9018,9020,9022,9024,9026,9028,9030,9032,9034],{"class":5249,"line":5256},[5247,9019,7515],{"class":5825},[5247,9021,5951],{"class":5870},[5247,9023,6055],{"class":5825},[5247,9025,6058],{"class":5885},[5247,9027,5948],{"class":5825},[5247,9029,7526],{"class":5870},[5247,9031,6055],{"class":5825},[5247,9033,7531],{"class":5885},[5247,9035,5924],{"class":5825},[5247,9037,9038,9041,9044,9046,9049,9051,9054,9056,9059],{"class":5249,"line":5262},[5247,9039,9040],{"class":5825},"scheduler = optim.lr_scheduler.CosineAnnealingLR(optimizer, ",[5247,9042,9043],{"class":5870},"T_max",[5247,9045,6055],{"class":5825},[5247,9047,9048],{"class":5885},"100",[5247,9050,5948],{"class":5825},[5247,9052,9053],{"class":5870},"eta_min",[5247,9055,6055],{"class":5825},[5247,9057,9058],{"class":5885},"1e-6",[5247,9060,5924],{"class":5825},[5247,9062,9063],{"class":5249,"line":5268},[5247,9064,5278],{"emptyLinePlaceholder":5277},[5247,9066,9067],{"class":5249,"line":5274},[5247,9068,9069],{"class":5825},"lr_history_cosine = []\n",[5247,9071,9072,9074,9076,9078,9080],{"class":5249,"line":5281},[5247,9073,6281],{"class":5821},[5247,9075,7599],{"class":5825},[5247,9077,5984],{"class":5821},[5247,9079,5987],{"class":5863},[5247,9081,7606],{"class":5825},[5247,9083,9084,9087,9089,9091,9093],{"class":5249,"line":5287},[5247,9085,9086],{"class":5825},"    lr_history_cosine.append(optimizer.param_groups[",[5247,9088,6216],{"class":5885},[5247,9090,7616],{"class":5825},[5247,9092,7619],{"class":6204},[5247,9094,6267],{"class":5825},[5247,9096,9097],{"class":5249,"line":5293},[5247,9098,7635],{"class":5825},[5247,9100,9101],{"class":5249,"line":5299},[5247,9102,7649],{"class":5825},[5247,9104,9105],{"class":5249,"line":5304},[5247,9106,5278],{"emptyLinePlaceholder":5277},[5247,9108,9109],{"class":5249,"line":5310},[5247,9110,9111],{"class":5853},"# Візуалізація всіх schedulers разом для порівняння\n",[5247,9113,9114,9116,9118,9120,9122,9124,9126,9128,9131,9133,9135],{"class":5249,"line":5316},[5247,9115,6125],{"class":5825},[5247,9117,5808],{"class":5885},[5247,9119,5948],{"class":5825},[5247,9121,6264],{"class":5885},[5247,9123,5948],{"class":5825},[5247,9125,6136],{"class":5870},[5247,9127,6139],{"class":5825},[5247,9129,9130],{"class":5885},"16",[5247,9132,5948],{"class":5825},[5247,9134,6147],{"class":5885},[5247,9136,6150],{"class":5825},[5247,9138,9139],{"class":5249,"line":5322},[5247,9140,5278],{"emptyLinePlaceholder":5277},[5247,9142,9143],{"class":5249,"line":5328},[5247,9144,9145],{"class":5853},"# Графік 1: CosineAnnealingLR\n",[5247,9147,9148,9151,9153],{"class":5249,"line":5334},[5247,9149,9150],{"class":5825},"ax = axes[",[5247,9152,6216],{"class":5885},[5247,9154,6272],{"class":5825},[5247,9156,9157,9160,9162,9164,9166,9168,9170,9172,9174,9176,9178,9180,9183],{"class":5249,"line":5340},[5247,9158,9159],{"class":5825},"ax.plot(lr_history_cosine, ",[5247,9161,6307],{"class":5870},[5247,9163,6055],{"class":5825},[5247,9165,6428],{"class":5885},[5247,9167,5948],{"class":5825},[5247,9169,6418],{"class":5870},[5247,9171,6055],{"class":5825},[5247,9173,6236],{"class":6204},[5247,9175,5948],{"class":5825},[5247,9177,6327],{"class":5870},[5247,9179,6055],{"class":5825},[5247,9181,9182],{"class":6204},"'CosineAnnealingLR'",[5247,9184,5924],{"class":5825},[5247,9186,9187,9190,9192,9194,9196,9198,9200],{"class":5249,"line":5346},[5247,9188,9189],{"class":5825},"ax.set_xlabel(",[5247,9191,7712],{"class":6204},[5247,9193,5948],{"class":5825},[5247,9195,6653],{"class":5870},[5247,9197,6055],{"class":5825},[5247,9199,6500],{"class":5885},[5247,9201,5924],{"class":5825},[5247,9203,9204,9207,9209,9211,9213,9215,9217],{"class":5249,"line":5352},[5247,9205,9206],{"class":5825},"ax.set_ylabel(",[5247,9208,7730],{"class":6204},[5247,9210,5948],{"class":5825},[5247,9212,6653],{"class":5870},[5247,9214,6055],{"class":5825},[5247,9216,6500],{"class":5885},[5247,9218,5924],{"class":5825},[5247,9220,9221,9224,9227,9229,9231,9233,9235,9237,9239,9241,9243],{"class":5249,"line":5358},[5247,9222,9223],{"class":5825},"ax.set_title(",[5247,9225,9226],{"class":6204},"'CosineAnnealingLR — плавна косинусоїда'",[5247,9228,5948],{"class":5825},[5247,9230,6653],{"class":5870},[5247,9232,6055],{"class":5825},[5247,9234,6565],{"class":5885},[5247,9236,5948],{"class":5825},[5247,9238,6721],{"class":5870},[5247,9240,6055],{"class":5825},[5247,9242,6726],{"class":6204},[5247,9244,5924],{"class":5825},[5247,9246,9247,9250,9252,9254,9256],{"class":5249,"line":5364},[5247,9248,9249],{"class":5825},"ax.grid(",[5247,9251,6317],{"class":5870},[5247,9253,6055],{"class":5825},[5247,9255,6322],{"class":5885},[5247,9257,5924],{"class":5825},[5247,9259,9260,9263,9265,9267,9269],{"class":5249,"line":5369},[5247,9261,9262],{"class":5825},"ax.legend(",[5247,9264,6653],{"class":5870},[5247,9266,6055],{"class":5825},[5247,9268,7805],{"class":5885},[5247,9270,5924],{"class":5825},[5247,9272,9273],{"class":5249,"line":5375},[5247,9274,5278],{"emptyLinePlaceholder":5277},[5247,9276,9277],{"class":5249,"line":5380},[5247,9278,9279],{"class":5853},"# Графік 2: Порівняння всіх schedulers\n",[5247,9281,9282,9284,9286],{"class":5249,"line":5386},[5247,9283,9150],{"class":5825},[5247,9285,5808],{"class":5885},[5247,9287,6272],{"class":5825},[5247,9289,9290,9293,9295,9297,9299,9301,9303,9305,9307,9309,9311,9313,9315],{"class":5249,"line":5392},[5247,9291,9292],{"class":5825},"ax.plot(lr_history_step, ",[5247,9294,6307],{"class":5870},[5247,9296,6055],{"class":5825},[5247,9298,6264],{"class":5885},[5247,9300,5948],{"class":5825},[5247,9302,6327],{"class":5870},[5247,9304,6055],{"class":5825},[5247,9306,7702],{"class":6204},[5247,9308,5948],{"class":5825},[5247,9310,6317],{"class":5870},[5247,9312,6055],{"class":5825},[5247,9314,6450],{"class":5885},[5247,9316,5924],{"class":5825},[5247,9318,9319,9322,9324,9326,9328,9330,9332,9334,9336,9338,9340,9342,9344],{"class":5249,"line":5398},[5247,9320,9321],{"class":5825},"ax.plot(lr_history_multistep, ",[5247,9323,6307],{"class":5870},[5247,9325,6055],{"class":5825},[5247,9327,6264],{"class":5885},[5247,9329,5948],{"class":5825},[5247,9331,6327],{"class":5870},[5247,9333,6055],{"class":5825},[5247,9335,8180],{"class":6204},[5247,9337,5948],{"class":5825},[5247,9339,6317],{"class":5870},[5247,9341,6055],{"class":5825},[5247,9343,6450],{"class":5885},[5247,9345,5924],{"class":5825},[5247,9347,9348,9351,9353,9355,9357,9359,9361,9363,9366,9368,9370,9372,9374],{"class":5249,"line":5404},[5247,9349,9350],{"class":5825},"ax.plot(lr_history_exp, ",[5247,9352,6307],{"class":5870},[5247,9354,6055],{"class":5825},[5247,9356,6264],{"class":5885},[5247,9358,5948],{"class":5825},[5247,9360,6327],{"class":5870},[5247,9362,6055],{"class":5825},[5247,9364,9365],{"class":6204},"'ExponentialLR'",[5247,9367,5948],{"class":5825},[5247,9369,6317],{"class":5870},[5247,9371,6055],{"class":5825},[5247,9373,6450],{"class":5885},[5247,9375,5924],{"class":5825},[5247,9377,9378,9380,9382,9384,9386,9388,9390,9392,9394,9396,9398,9400,9402],{"class":5249,"line":5409},[5247,9379,9159],{"class":5825},[5247,9381,6307],{"class":5870},[5247,9383,6055],{"class":5825},[5247,9385,6264],{"class":5885},[5247,9387,5948],{"class":5825},[5247,9389,6327],{"class":5870},[5247,9391,6055],{"class":5825},[5247,9393,9182],{"class":6204},[5247,9395,5948],{"class":5825},[5247,9397,6317],{"class":5870},[5247,9399,6055],{"class":5825},[5247,9401,6450],{"class":5885},[5247,9403,5924],{"class":5825},[5247,9405,9406],{"class":5249,"line":5414},[5247,9407,5278],{"emptyLinePlaceholder":5277},[5247,9409,9410,9412,9414,9416,9418,9420,9422],{"class":5249,"line":5419},[5247,9411,9189],{"class":5825},[5247,9413,7712],{"class":6204},[5247,9415,5948],{"class":5825},[5247,9417,6653],{"class":5870},[5247,9419,6055],{"class":5825},[5247,9421,6500],{"class":5885},[5247,9423,5924],{"class":5825},[5247,9425,9426,9428,9430,9432,9434,9436,9438],{"class":5249,"line":5425},[5247,9427,9206],{"class":5825},[5247,9429,7730],{"class":6204},[5247,9431,5948],{"class":5825},[5247,9433,6653],{"class":5870},[5247,9435,6055],{"class":5825},[5247,9437,6500],{"class":5885},[5247,9439,5924],{"class":5825},[5247,9441,9442,9444,9447,9449,9451,9453,9455,9457,9459,9461,9463],{"class":5249,"line":5430},[5247,9443,9223],{"class":5825},[5247,9445,9446],{"class":6204},"'Порівняння всіх schedulers'",[5247,9448,5948],{"class":5825},[5247,9450,6653],{"class":5870},[5247,9452,6055],{"class":5825},[5247,9454,6565],{"class":5885},[5247,9456,5948],{"class":5825},[5247,9458,6721],{"class":5870},[5247,9460,6055],{"class":5825},[5247,9462,6726],{"class":6204},[5247,9464,5924],{"class":5825},[5247,9466,9467,9470,9472],{"class":5249,"line":5436},[5247,9468,9469],{"class":5825},"ax.set_yscale(",[5247,9471,7774],{"class":6204},[5247,9473,5924],{"class":5825},[5247,9475,9476,9478,9480,9482,9484],{"class":5249,"line":5442},[5247,9477,9249],{"class":5825},[5247,9479,6317],{"class":5870},[5247,9481,6055],{"class":5825},[5247,9483,6322],{"class":5885},[5247,9485,5924],{"class":5825},[5247,9487,9488,9490,9492,9494,9496],{"class":5249,"line":5448},[5247,9489,9262],{"class":5825},[5247,9491,6653],{"class":5870},[5247,9493,6055],{"class":5825},[5247,9495,6555],{"class":5885},[5247,9497,5924],{"class":5825},[5247,9499,9500],{"class":5249,"line":5454},[5247,9501,5278],{"emptyLinePlaceholder":5277},[5247,9503,9504],{"class":5249,"line":5460},[5247,9505,6782],{"class":5825},[5247,9507,9508],{"class":5249,"line":5466},[5247,9509,6788],{"class":5825},[7107,9511,9512],{"v-slot:output":5242},[7112,9513],{"alt":9514,"className":9515,"src":9516},"Порівняння schedulers: StepLR (різкий), ExponentialLR та CosineAnnealingLR (плавні)",[7116],"\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling\u002F05.png",[5191,9518,9519],{},[5195,9520,7968],{},[5625,9522,9523,9530,9533],{},[5628,9524,9525,9526,9529],{},"✅ ",[5195,9527,9528],{},"Найплавніша"," зміна LR (без різких стрибків)",[5628,9531,9532],{},"✅ Математично обґрунтована (cosine decay)",[5628,9534,9535],{},"✅ Популярний вибір у сучасних дослідженнях (BERT, GPT, EfficientNet)",[5191,9537,9538],{},[5195,9539,7984],{},[5625,9541,9542],{},[5628,9543,9544,9545],{},"❌ Потрібно заздалегідь знати загальну кількість епох ",[5200,9546],{"tex":8975,":inline":5203},[5191,9548,9549,9551],{},[5195,9550,8000],{}," За замовчуванням для сучасних архітектур (Transformers, EfficientNet). Особливо для довгих тренувань (100+ епох).",[9553,9554,9555,9560,9563,9578],"tip",{},[5191,9556,9557],{},[5195,9558,9559],{},"Чому косинусоїда?",[5191,9561,9562],{},"Косинусоїдальне зменшення має дві приємні властивості:",[9564,9565,9566,9572],"ol",{},[5628,9567,9568,9571],{},[5195,9569,9570],{},"Швидкий старт:"," На початку LR зменшується швидше (крутий схил косинуса)",[5628,9573,9574,9577],{},[5195,9575,9576],{},"Плавне завершення:"," Наближаючись до мінімуму, зменшення сповільнюється (пологий кінець косинуса)",[5191,9579,9580],{},"Це природно відповідає потребам оптимізації: швидко рухаємось на початку, обережно fine-tune наприкінці.",[5712,9582],{},[5544,9584,9586],{"id":9585},"_5-reducelronplateau-адаптивне-зменшення","5. ReduceLROnPlateau — адаптивне зменшення",[5191,9588,9589,9591,9592,9595,9596,7347],{},[5195,9590,7338],{}," Зменшувати LR ",[5195,9593,9594],{},"автоматично",", коли метрика (val loss або val accuracy) перестає покращуватися протягом ",[5200,9597],{"tex":7346,":inline":5203},[5191,9599,9600,9603,9604,9607,9608,9611],{},[5195,9601,9602],{},"Відмінність від попередніх:"," Це ",[5195,9605,9606],{},"динамічний"," scheduler — він реагує на ",[5195,9609,9610],{},"фактичний прогрес навчання",", а не на фіксований графік епох.",[5796,9613,9614,10428],{"execution-count":6171},[5237,9615,9617],{"className":5812,"code":9616,"language":5814,"meta":5242,"style":5242},"# ReduceLROnPlateau scheduler\noptimizer = optim.SGD(model.parameters(), lr=0.1, momentum=0.9)\nscheduler = optim.lr_scheduler.ReduceLROnPlateau(\n    optimizer,\n    mode='min',      # Моніторимо мінімізацію loss (для accuracy — mode='max')\n    factor=0.5,      # Множити LR на 0.5 (зменшення удвічі)\n    patience=10,     # Чекати 10 епох без покращення перед зменшенням\n    verbose=False,   # Виводити повідомлення при зміні LR\n    min_lr=1e-6      # Мінімальне значення LR\n)\n\n# Симуляція val_loss (спочатку зменшується, потім plateau, потім знову зменшується)\nnp.random.seed(42)\nsimulated_val_loss = []\nlr_history_plateau = []\n\n# Епохи 0-30: швидке зменшення loss\nsimulated_val_loss.extend(np.linspace(2.3, 0.8, 30) + np.random.randn(30) * 0.05)\n\n# Епохи 30-50: plateau (loss майже не змінюється)\nsimulated_val_loss.extend(np.ones(20) * 0.8 + np.random.randn(20) * 0.03)\n\n# Епохи 50-70: знову зменшення після зменшення LR\nsimulated_val_loss.extend(np.linspace(0.8, 0.4, 20) + np.random.randn(20) * 0.02)\n\n# Епохи 70-100: ще один plateau\nsimulated_val_loss.extend(np.ones(30) * 0.4 + np.random.randn(30) * 0.02)\n\nfor epoch in range(100):\n    lr_history_plateau.append(optimizer.param_groups[0]['lr'])\n    optimizer.step()\n    \n    # Передаємо поточну val_loss у scheduler\n    scheduler.step(simulated_val_loss[epoch])\n\n# Візуалізація\nfig, axes = plt.subplots(2, 1, figsize=(14, 10), sharex=True)\n\n# Графік 1: Val Loss\nax = axes[0]\nax.plot(simulated_val_loss, linewidth=2, color='#ef4444', label='Validation Loss')\nax.set_ylabel('Validation Loss', fontsize=12)\nax.set_title('ReduceLROnPlateau — адаптивне реагування на plateau', fontsize=14, fontweight='bold')\nax.grid(alpha=0.3)\nax.legend(fontsize=11)\n\n# Графік 2: Learning Rate\nax = axes[1]\nax.plot(lr_history_plateau, linewidth=2.5, color='#8b5cf6', label='Learning Rate')\nax.set_xlabel('Epoch', fontsize=12)\nax.set_ylabel('Learning Rate', fontsize=12)\nax.set_yscale('log')\nax.grid(alpha=0.3)\nax.legend(fontsize=11)\n\n# Позначимо моменти зміни LR\nlr_changes = []\nfor i in range(1, len(lr_history_plateau)):\n    if lr_history_plateau[i] != lr_history_plateau[i-1]:\n        lr_changes.append(i)\n        ax.axvline(x=i, color='red', linestyle='--', alpha=0.5, linewidth=1.5)\n\nplt.tight_layout()\nplt.show()\n\nprint(f\"📊 ReduceLROnPlateau:\")\nprint(f\"├─ Початковий LR: {lr_history_plateau[0]:.6f}\")\nfor change_epoch in lr_changes:\n    print(f\"├─ Епоха {change_epoch}: LR зменшено до {lr_history_plateau[change_epoch]:.6f}\")\nprint(f\"└─ Фінальний LR: {lr_history_plateau[-1]:.6f}\")\n",[5244,9618,9619,9624,9644,9649,9654,9670,9684,9699,9715,9727,9731,9735,9740,9750,9755,9760,9764,9769,9798,9802,9807,9830,9834,9839,9865,9869,9874,9894,9898,9914,9927,9931,9935,9940,9945,9949,9953,9987,9991,9996,10004,10034,10050,10075,10087,10099,10103,10108,10116,10145,10161,10177,10185,10197,10209,10213,10218,10223,10244,10256,10261,10303,10307,10311,10315,10319,10332,10358,10370,10402],{"__ignoreMap":5242},[5247,9620,9621],{"class":5249,"line":5250},[5247,9622,9623],{"class":5853},"# ReduceLROnPlateau scheduler\n",[5247,9625,9626,9628,9630,9632,9634,9636,9638,9640,9642],{"class":5249,"line":5256},[5247,9627,7515],{"class":5825},[5247,9629,5951],{"class":5870},[5247,9631,6055],{"class":5825},[5247,9633,6058],{"class":5885},[5247,9635,5948],{"class":5825},[5247,9637,7526],{"class":5870},[5247,9639,6055],{"class":5825},[5247,9641,7531],{"class":5885},[5247,9643,5924],{"class":5825},[5247,9645,9646],{"class":5249,"line":5262},[5247,9647,9648],{"class":5825},"scheduler = optim.lr_scheduler.ReduceLROnPlateau(\n",[5247,9650,9651],{"class":5249,"line":5268},[5247,9652,9653],{"class":5825},"    optimizer,\n",[5247,9655,9656,9659,9661,9664,9667],{"class":5249,"line":5274},[5247,9657,9658],{"class":5870},"    mode",[5247,9660,6055],{"class":5825},[5247,9662,9663],{"class":6204},"'min'",[5247,9665,9666],{"class":5825},",      ",[5247,9668,9669],{"class":5853},"# Моніторимо мінімізацію loss (для accuracy — mode='max')\n",[5247,9671,9672,9675,9677,9679,9681],{"class":5249,"line":5281},[5247,9673,9674],{"class":5870},"    factor",[5247,9676,6055],{"class":5825},[5247,9678,6080],{"class":5885},[5247,9680,9666],{"class":5825},[5247,9682,9683],{"class":5853},"# Множити LR на 0.5 (зменшення удвічі)\n",[5247,9685,9686,9689,9691,9693,9696],{"class":5249,"line":5287},[5247,9687,9688],{"class":5870},"    patience",[5247,9690,6055],{"class":5825},[5247,9692,6555],{"class":5885},[5247,9694,9695],{"class":5825},",     ",[5247,9697,9698],{"class":5853},"# Чекати 10 епох без покращення перед зменшенням\n",[5247,9700,9701,9704,9706,9709,9712],{"class":5249,"line":5293},[5247,9702,9703],{"class":5870},"    verbose",[5247,9705,6055],{"class":5825},[5247,9707,9708],{"class":5859},"False",[5247,9710,9711],{"class":5825},",   ",[5247,9713,9714],{"class":5853},"# Виводити повідомлення при зміні LR\n",[5247,9716,9717,9720,9722,9724],{"class":5249,"line":5299},[5247,9718,9719],{"class":5870},"    min_lr",[5247,9721,6055],{"class":5825},[5247,9723,9058],{"class":5885},[5247,9725,9726],{"class":5853},"      # Мінімальне значення LR\n",[5247,9728,9729],{"class":5249,"line":5304},[5247,9730,5924],{"class":5825},[5247,9732,9733],{"class":5249,"line":5310},[5247,9734,5278],{"emptyLinePlaceholder":5277},[5247,9736,9737],{"class":5249,"line":5316},[5247,9738,9739],{"class":5853},"# Симуляція val_loss (спочатку зменшується, потім plateau, потім знову зменшується)\n",[5247,9741,9742,9745,9748],{"class":5249,"line":5322},[5247,9743,9744],{"class":5825},"np.random.seed(",[5247,9746,9747],{"class":5885},"42",[5247,9749,5924],{"class":5825},[5247,9751,9752],{"class":5249,"line":5328},[5247,9753,9754],{"class":5825},"simulated_val_loss = []\n",[5247,9756,9757],{"class":5249,"line":5334},[5247,9758,9759],{"class":5825},"lr_history_plateau = []\n",[5247,9761,9762],{"class":5249,"line":5340},[5247,9763,5278],{"emptyLinePlaceholder":5277},[5247,9765,9766],{"class":5249,"line":5346},[5247,9767,9768],{"class":5853},"# Епохи 0-30: швидке зменшення loss\n",[5247,9770,9771,9774,9777,9779,9781,9783,9785,9788,9790,9793,9796],{"class":5249,"line":5352},[5247,9772,9773],{"class":5825},"simulated_val_loss.extend(np.linspace(",[5247,9775,9776],{"class":5885},"2.3",[5247,9778,5948],{"class":5825},[5247,9780,6450],{"class":5885},[5247,9782,5948],{"class":5825},[5247,9784,7555],{"class":5885},[5247,9786,9787],{"class":5825},") + np.random.randn(",[5247,9789,7555],{"class":5885},[5247,9791,9792],{"class":5825},") * ",[5247,9794,9795],{"class":5885},"0.05",[5247,9797,5924],{"class":5825},[5247,9799,9800],{"class":5249,"line":5358},[5247,9801,5278],{"emptyLinePlaceholder":5277},[5247,9803,9804],{"class":5249,"line":5364},[5247,9805,9806],{"class":5853},"# Епохи 30-50: plateau (loss майже не змінюється)\n",[5247,9808,9809,9812,9814,9816,9818,9821,9823,9825,9828],{"class":5249,"line":5369},[5247,9810,9811],{"class":5825},"simulated_val_loss.extend(np.ones(",[5247,9813,6369],{"class":5885},[5247,9815,9792],{"class":5825},[5247,9817,6450],{"class":5885},[5247,9819,9820],{"class":5825}," + np.random.randn(",[5247,9822,6369],{"class":5885},[5247,9824,9792],{"class":5825},[5247,9826,9827],{"class":5885},"0.03",[5247,9829,5924],{"class":5825},[5247,9831,9832],{"class":5249,"line":5375},[5247,9833,5278],{"emptyLinePlaceholder":5277},[5247,9835,9836],{"class":5249,"line":5380},[5247,9837,9838],{"class":5853},"# Епохи 50-70: знову зменшення після зменшення LR\n",[5247,9840,9841,9843,9845,9847,9850,9852,9854,9856,9858,9860,9863],{"class":5249,"line":5386},[5247,9842,9773],{"class":5825},[5247,9844,6450],{"class":5885},[5247,9846,5948],{"class":5825},[5247,9848,9849],{"class":5885},"0.4",[5247,9851,5948],{"class":5825},[5247,9853,6369],{"class":5885},[5247,9855,9787],{"class":5825},[5247,9857,6369],{"class":5885},[5247,9859,9792],{"class":5825},[5247,9861,9862],{"class":5885},"0.02",[5247,9864,5924],{"class":5825},[5247,9866,9867],{"class":5249,"line":5392},[5247,9868,5278],{"emptyLinePlaceholder":5277},[5247,9870,9871],{"class":5249,"line":5398},[5247,9872,9873],{"class":5853},"# Епохи 70-100: ще один plateau\n",[5247,9875,9876,9878,9880,9882,9884,9886,9888,9890,9892],{"class":5249,"line":5404},[5247,9877,9811],{"class":5825},[5247,9879,7555],{"class":5885},[5247,9881,9792],{"class":5825},[5247,9883,9849],{"class":5885},[5247,9885,9820],{"class":5825},[5247,9887,7555],{"class":5885},[5247,9889,9792],{"class":5825},[5247,9891,9862],{"class":5885},[5247,9893,5924],{"class":5825},[5247,9895,9896],{"class":5249,"line":5409},[5247,9897,5278],{"emptyLinePlaceholder":5277},[5247,9899,9900,9902,9904,9906,9908,9910,9912],{"class":5249,"line":5414},[5247,9901,6281],{"class":5821},[5247,9903,7599],{"class":5825},[5247,9905,5984],{"class":5821},[5247,9907,5987],{"class":5863},[5247,9909,5867],{"class":5825},[5247,9911,9048],{"class":5885},[5247,9913,5874],{"class":5825},[5247,9915,9916,9919,9921,9923,9925],{"class":5249,"line":5419},[5247,9917,9918],{"class":5825},"    lr_history_plateau.append(optimizer.param_groups[",[5247,9920,6216],{"class":5885},[5247,9922,7616],{"class":5825},[5247,9924,7619],{"class":6204},[5247,9926,6267],{"class":5825},[5247,9928,9929],{"class":5249,"line":5425},[5247,9930,7635],{"class":5825},[5247,9932,9933],{"class":5249,"line":5430},[5247,9934,5973],{"class":5825},[5247,9936,9937],{"class":5249,"line":5436},[5247,9938,9939],{"class":5853},"    # Передаємо поточну val_loss у scheduler\n",[5247,9941,9942],{"class":5249,"line":5442},[5247,9943,9944],{"class":5825},"    scheduler.step(simulated_val_loss[epoch])\n",[5247,9946,9947],{"class":5249,"line":5448},[5247,9948,5278],{"emptyLinePlaceholder":5277},[5247,9950,9951],{"class":5249,"line":5454},[5247,9952,6120],{"class":5853},[5247,9954,9955,9957,9959,9961,9963,9965,9967,9969,9971,9973,9975,9977,9980,9982,9985],{"class":5249,"line":5460},[5247,9956,6125],{"class":5825},[5247,9958,6264],{"class":5885},[5247,9960,5948],{"class":5825},[5247,9962,5808],{"class":5885},[5247,9964,5948],{"class":5825},[5247,9966,6136],{"class":5870},[5247,9968,6139],{"class":5825},[5247,9970,6565],{"class":5885},[5247,9972,5948],{"class":5825},[5247,9974,6555],{"class":5885},[5247,9976,6640],{"class":5825},[5247,9978,9979],{"class":5870},"sharex",[5247,9981,6055],{"class":5825},[5247,9983,9984],{"class":5859},"True",[5247,9986,5924],{"class":5825},[5247,9988,9989],{"class":5249,"line":5466},[5247,9990,5278],{"emptyLinePlaceholder":5277},[5247,9992,9993],{"class":5249,"line":5472},[5247,9994,9995],{"class":5853},"# Графік 1: Val Loss\n",[5247,9997,9998,10000,10002],{"class":5249,"line":5477},[5247,9999,9150],{"class":5825},[5247,10001,6216],{"class":5885},[5247,10003,6272],{"class":5825},[5247,10005,10006,10009,10011,10013,10015,10017,10019,10021,10023,10025,10027,10029,10032],{"class":5249,"line":5482},[5247,10007,10008],{"class":5825},"ax.plot(simulated_val_loss, ",[5247,10010,6307],{"class":5870},[5247,10012,6055],{"class":5825},[5247,10014,6264],{"class":5885},[5247,10016,5948],{"class":5825},[5247,10018,6418],{"class":5870},[5247,10020,6055],{"class":5825},[5247,10022,6259],{"class":6204},[5247,10024,5948],{"class":5825},[5247,10026,6327],{"class":5870},[5247,10028,6055],{"class":5825},[5247,10030,10031],{"class":6204},"'Validation Loss'",[5247,10033,5924],{"class":5825},[5247,10035,10036,10038,10040,10042,10044,10046,10048],{"class":5249,"line":5488},[5247,10037,9206],{"class":5825},[5247,10039,10031],{"class":6204},[5247,10041,5948],{"class":5825},[5247,10043,6653],{"class":5870},[5247,10045,6055],{"class":5825},[5247,10047,6500],{"class":5885},[5247,10049,5924],{"class":5825},[5247,10051,10052,10054,10057,10059,10061,10063,10065,10067,10069,10071,10073],{"class":5249,"line":5493},[5247,10053,9223],{"class":5825},[5247,10055,10056],{"class":6204},"'ReduceLROnPlateau — адаптивне реагування на plateau'",[5247,10058,5948],{"class":5825},[5247,10060,6653],{"class":5870},[5247,10062,6055],{"class":5825},[5247,10064,6565],{"class":5885},[5247,10066,5948],{"class":5825},[5247,10068,6721],{"class":5870},[5247,10070,6055],{"class":5825},[5247,10072,6726],{"class":6204},[5247,10074,5924],{"class":5825},[5247,10076,10077,10079,10081,10083,10085],{"class":5249,"line":5499},[5247,10078,9249],{"class":5825},[5247,10080,6317],{"class":5870},[5247,10082,6055],{"class":5825},[5247,10084,6322],{"class":5885},[5247,10086,5924],{"class":5825},[5247,10088,10089,10091,10093,10095,10097],{"class":5249,"line":5505},[5247,10090,9262],{"class":5825},[5247,10092,6653],{"class":5870},[5247,10094,6055],{"class":5825},[5247,10096,7805],{"class":5885},[5247,10098,5924],{"class":5825},[5247,10100,10101],{"class":5249,"line":5510},[5247,10102,5278],{"emptyLinePlaceholder":5277},[5247,10104,10105],{"class":5249,"line":5516},[5247,10106,10107],{"class":5853},"# Графік 2: Learning Rate\n",[5247,10109,10110,10112,10114],{"class":5249,"line":5522},[5247,10111,9150],{"class":5825},[5247,10113,5808],{"class":5885},[5247,10115,6272],{"class":5825},[5247,10117,10118,10121,10123,10125,10127,10129,10131,10133,10135,10137,10139,10141,10143],{"class":5249,"line":5528},[5247,10119,10120],{"class":5825},"ax.plot(lr_history_plateau, ",[5247,10122,6307],{"class":5870},[5247,10124,6055],{"class":5825},[5247,10126,6428],{"class":5885},[5247,10128,5948],{"class":5825},[5247,10130,6418],{"class":5870},[5247,10132,6055],{"class":5825},[5247,10134,8171],{"class":6204},[5247,10136,5948],{"class":5825},[5247,10138,6327],{"class":5870},[5247,10140,6055],{"class":5825},[5247,10142,7730],{"class":6204},[5247,10144,5924],{"class":5825},[5247,10146,10147,10149,10151,10153,10155,10157,10159],{"class":5249,"line":5534},[5247,10148,9189],{"class":5825},[5247,10150,7712],{"class":6204},[5247,10152,5948],{"class":5825},[5247,10154,6653],{"class":5870},[5247,10156,6055],{"class":5825},[5247,10158,6500],{"class":5885},[5247,10160,5924],{"class":5825},[5247,10162,10163,10165,10167,10169,10171,10173,10175],{"class":5249,"line":5539},[5247,10164,9206],{"class":5825},[5247,10166,7730],{"class":6204},[5247,10168,5948],{"class":5825},[5247,10170,6653],{"class":5870},[5247,10172,6055],{"class":5825},[5247,10174,6500],{"class":5885},[5247,10176,5924],{"class":5825},[5247,10178,10179,10181,10183],{"class":5249,"line":6401},[5247,10180,9469],{"class":5825},[5247,10182,7774],{"class":6204},[5247,10184,5924],{"class":5825},[5247,10186,10187,10189,10191,10193,10195],{"class":5249,"line":6407},[5247,10188,9249],{"class":5825},[5247,10190,6317],{"class":5870},[5247,10192,6055],{"class":5825},[5247,10194,6322],{"class":5885},[5247,10196,5924],{"class":5825},[5247,10198,10199,10201,10203,10205,10207],{"class":5249,"line":6434},[5247,10200,9262],{"class":5825},[5247,10202,6653],{"class":5870},[5247,10204,6055],{"class":5825},[5247,10206,7805],{"class":5885},[5247,10208,5924],{"class":5825},[5247,10210,10211],{"class":5249,"line":6464},[5247,10212,5278],{"emptyLinePlaceholder":5277},[5247,10214,10215],{"class":5249,"line":6469},[5247,10216,10217],{"class":5853},"# Позначимо моменти зміни LR\n",[5247,10219,10220],{"class":5249,"line":6475},[5247,10221,10222],{"class":5825},"lr_changes = []\n",[5247,10224,10225,10227,10229,10231,10233,10235,10237,10239,10241],{"class":5249,"line":6523},[5247,10226,6281],{"class":5821},[5247,10228,6539],{"class":5825},[5247,10230,5984],{"class":5821},[5247,10232,5987],{"class":5863},[5247,10234,5867],{"class":5825},[5247,10236,5808],{"class":5885},[5247,10238,5948],{"class":5825},[5247,10240,6570],{"class":5863},[5247,10242,10243],{"class":5825},"(lr_history_plateau)):\n",[5247,10245,10246,10249,10252,10254],{"class":5249,"line":6528},[5247,10247,10248],{"class":5821},"    if",[5247,10250,10251],{"class":5825}," lr_history_plateau[i] != lr_history_plateau[i-",[5247,10253,5808],{"class":5885},[5247,10255,8215],{"class":5825},[5247,10257,10258],{"class":5249,"line":6534},[5247,10259,10260],{"class":5825},"        lr_changes.append(i)\n",[5247,10262,10263,10266,10268,10271,10273,10275,10277,10279,10281,10283,10285,10287,10289,10291,10293,10295,10297,10299,10301],{"class":5249,"line":6581},[5247,10264,10265],{"class":5825},"        ax.axvline(",[5247,10267,8223],{"class":5870},[5247,10269,10270],{"class":5825},"=i, ",[5247,10272,6418],{"class":5870},[5247,10274,6055],{"class":5825},[5247,10276,8233],{"class":6204},[5247,10278,5948],{"class":5825},[5247,10280,8238],{"class":5870},[5247,10282,6055],{"class":5825},[5247,10284,8243],{"class":6204},[5247,10286,5948],{"class":5825},[5247,10288,6317],{"class":5870},[5247,10290,6055],{"class":5825},[5247,10292,6080],{"class":5885},[5247,10294,5948],{"class":5825},[5247,10296,6307],{"class":5870},[5247,10298,6055],{"class":5825},[5247,10300,6312],{"class":5885},[5247,10302,5924],{"class":5825},[5247,10304,10305],{"class":5249,"line":6595},[5247,10306,5278],{"emptyLinePlaceholder":5277},[5247,10308,10309],{"class":5249,"line":6626},[5247,10310,6782],{"class":5825},[5247,10312,10313],{"class":5249,"line":6663},[5247,10314,6788],{"class":5825},[5247,10316,10317],{"class":5249,"line":6668},[5247,10318,5278],{"emptyLinePlaceholder":5277},[5247,10320,10321,10323,10325,10327,10330],{"class":5249,"line":6687},[5247,10322,6805],{"class":5863},[5247,10324,5867],{"class":5825},[5247,10326,6601],{"class":5859},[5247,10328,10329],{"class":6204},"\"📊 ReduceLROnPlateau:\"",[5247,10331,5924],{"class":5825},[5247,10333,10334,10336,10338,10340,10343,10345,10348,10350,10352,10354,10356],{"class":5249,"line":6706},[5247,10335,6805],{"class":5863},[5247,10337,5867],{"class":5825},[5247,10339,6601],{"class":5859},[5247,10341,10342],{"class":6204},"\"├─ Початковий LR: ",[5247,10344,6607],{"class":5859},[5247,10346,10347],{"class":5825},"lr_history_plateau[",[5247,10349,6216],{"class":5885},[5247,10351,7851],{"class":5825},[5247,10353,8780],{"class":5859},[5247,10355,6817],{"class":6204},[5247,10357,5924],{"class":5825},[5247,10359,10360,10362,10365,10367],{"class":5249,"line":6731},[5247,10361,6281],{"class":5821},[5247,10363,10364],{"class":5825}," change_epoch ",[5247,10366,5984],{"class":5821},[5247,10368,10369],{"class":5825}," lr_changes:\n",[5247,10371,10372,10374,10376,10378,10381,10383,10386,10388,10391,10393,10396,10398,10400],{"class":5249,"line":6745},[5247,10373,7058],{"class":5863},[5247,10375,5867],{"class":5825},[5247,10377,6601],{"class":5859},[5247,10379,10380],{"class":6204},"\"├─ Епоха ",[5247,10382,6607],{"class":5859},[5247,10384,10385],{"class":5825},"change_epoch",[5247,10387,6613],{"class":5859},[5247,10389,10390],{"class":6204},": LR зменшено до ",[5247,10392,6607],{"class":5859},[5247,10394,10395],{"class":5825},"lr_history_plateau[change_epoch]",[5247,10397,8780],{"class":5859},[5247,10399,6817],{"class":6204},[5247,10401,5924],{"class":5825},[5247,10403,10404,10406,10408,10410,10413,10415,10418,10420,10422,10424,10426],{"class":5249,"line":6759},[5247,10405,6805],{"class":5863},[5247,10407,5867],{"class":5825},[5247,10409,6601],{"class":5859},[5247,10411,10412],{"class":6204},"\"└─ Фінальний LR: ",[5247,10414,6607],{"class":5859},[5247,10416,10417],{"class":5825},"lr_history_plateau[-",[5247,10419,5808],{"class":5885},[5247,10421,7851],{"class":5825},[5247,10423,8780],{"class":5859},[5247,10425,6817],{"class":6204},[5247,10427,5924],{"class":5825},[7107,10429,10430,10437,10442],{"v-slot:output":5242},[5191,10431,10432],{},[7112,10433],{"alt":10434,"className":10435,"src":10436},"ReduceLROnPlateau: автоматичне зменшення LR при зупинці прогресу",[7116],"\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling\u002F06.png",[5191,10438,7120,10439],{},[5195,10440,10441],{},"ReduceLROnPlateau:",[5625,10443,10444,10447,10450,10453],{},[5628,10445,10446],{},"Початковий LR: 0.100000",[5628,10448,10449],{},"Епоха 40: LR зменшено до 0.050000 (перший plateau)",[5628,10451,10452],{},"Епоха 80: LR зменшено до 0.025000 (другий plateau)",[5628,10454,10455],{},"Фінальний LR: 0.025000",[5191,10457,10458],{},[5195,10459,7968],{},[5625,10461,10462,10468,10471],{},[5628,10463,9525,10464,10467],{},[5195,10465,10466],{},"Автоматичність:"," не потрібно вгадувати епохи для зменшення",[5628,10469,10470],{},"✅ Адаптується до фактичного прогресу моделі",[5628,10472,10473],{},"✅ Безпечний — зменшує LR лише коли справді застряємо",[5191,10475,10476],{},[5195,10477,7984],{},[5625,10479,10480,10487],{},[5628,10481,10482,10483,10486],{},"❌ Може бути консервативним (чекає ",[5244,10484,10485],{},"patience"," епох)",[5628,10488,10489],{},"❌ Залежить від шуму у val_loss (може спрацювати хибно)",[5191,10491,10492,10494],{},[5195,10493,8000],{}," Коли важко передбачити, коли модель зупиниться у прогресі. Ідеально для перших експериментів з новою архітектурою або датасетом.",[5712,10496],{},[5186,10498,10500],{"id":10499},"advanced-техніки-warm-up-та-warm-restarts","Advanced техніки — Warm-up та Warm Restarts",[5191,10502,10503,10504,10507,10508,5789],{},"Тепер розглянемо дві потужні advanced техніки, що використовуються у cutting-edge дослідженнях: ",[5195,10505,10506],{},"Learning Rate Warm-up"," та ",[5195,10509,10510],{},"SGDR (Stochastic Gradient Descent with Warm Restarts)",[5544,10512,10514],{"id":10513},"learning-rate-warm-up-обережний-старт","Learning Rate Warm-up — обережний старт",[5191,10516,10517,10519,10520,10523],{},[5195,10518,7228],{}," На самому початку навчання ваги ініціалізовані випадково (навіть з He\u002FXavier initialization). Якщо одразу застосувати великий LR (наприклад, 0.1), градієнти можуть бути ",[5195,10521,10522],{},"нестабільними"," та спричинити divergence, особливо для дуже глибоких мереж або великих batch sizes.",[5191,10525,10526,10529,10530,10533,10534,10536],{},[5195,10527,10528],{},"Ідея Warm-up:"," Починати з дуже малого LR (наприклад, 1e-5) та ",[5195,10531,10532],{},"поступово збільшувати"," його до цільового значення (0.1) протягом перших ",[5200,10535],{"tex":7346,":inline":5203}," епох або ітерацій.",[5233,10538,10540],{"alt":10539},"Learning Rate Warm-up стратегія",[5237,10541,10543],{"className":5239,"code":10542,"language":5241,"meta":5242,"style":5242},"@startuml\nskinparam style plain\nskinparam backgroundColor #FFFFFF\nskinparam defaultFontName \"Arial\"\n\n!define WARMUP_COLOR #FEF3C7\n!define MAIN_COLOR #DCFCE7\n!define DECAY_COLOR #E0E7FF\n\nrectangle \"Warm-up Phase\\n(епохи 0-5)\" as warmup #WARMUP_COLOR {\n  note right\n    🔥 Поступове збільшення\n    LR: 1e-5 → 0.1\n    \n    Чому? Ваги випадкові,\n    градієнти нестабільні.\n    Починаємо обережно.\n  end note\n}\n\nrectangle \"Main Training\\n(епохи 5-80)\" as main #MAIN_COLOR {\n  note right\n    ⚡ Повна швидкість\n    LR: 0.1 (фіксований)\n    \n    Модель швидко навчається,\n    ваги стабілізувалися.\n  end note\n}\n\nrectangle \"Decay Phase\\n(епохи 80-120)\" as decay #DECAY_COLOR {\n  note right\n    📉 Зменшення LR\n    LR: 0.1 → 0.01 → 0.001\n    \n    Fine-tuning біля мінімуму.\n  end note\n}\n\nwarmup -down-> main : Збільшення\\nдо цільового LR\nmain -down-> decay : Scheduler\\n(StepLR \u002F Cosine)\n\n@enduml\n",[5244,10544,10545,10549,10553,10557,10561,10565,10570,10575,10580,10584,10589,10594,10599,10604,10608,10613,10618,10623,10628,10632,10636,10641,10645,10650,10655,10659,10664,10669,10673,10677,10681,10686,10690,10695,10700,10704,10709,10713,10717,10721,10726,10731,10735],{"__ignoreMap":5242},[5247,10546,10547],{"class":5249,"line":5250},[5247,10548,5253],{},[5247,10550,10551],{"class":5249,"line":5256},[5247,10552,5259],{},[5247,10554,10555],{"class":5249,"line":5262},[5247,10556,5265],{},[5247,10558,10559],{"class":5249,"line":5268},[5247,10560,5271],{},[5247,10562,10563],{"class":5249,"line":5274},[5247,10564,5278],{"emptyLinePlaceholder":5277},[5247,10566,10567],{"class":5249,"line":5281},[5247,10568,10569],{},"!define WARMUP_COLOR #FEF3C7\n",[5247,10571,10572],{"class":5249,"line":5287},[5247,10573,10574],{},"!define MAIN_COLOR #DCFCE7\n",[5247,10576,10577],{"class":5249,"line":5293},[5247,10578,10579],{},"!define DECAY_COLOR #E0E7FF\n",[5247,10581,10582],{"class":5249,"line":5299},[5247,10583,5278],{"emptyLinePlaceholder":5277},[5247,10585,10586],{"class":5249,"line":5304},[5247,10587,10588],{},"rectangle \"Warm-up Phase\\n(епохи 0-5)\" as warmup #WARMUP_COLOR {\n",[5247,10590,10591],{"class":5249,"line":5310},[5247,10592,10593],{},"  note right\n",[5247,10595,10596],{"class":5249,"line":5316},[5247,10597,10598],{},"    🔥 Поступове збільшення\n",[5247,10600,10601],{"class":5249,"line":5322},[5247,10602,10603],{},"    LR: 1e-5 → 0.1\n",[5247,10605,10606],{"class":5249,"line":5328},[5247,10607,5973],{},[5247,10609,10610],{"class":5249,"line":5334},[5247,10611,10612],{},"    Чому? Ваги випадкові,\n",[5247,10614,10615],{"class":5249,"line":5340},[5247,10616,10617],{},"    градієнти нестабільні.\n",[5247,10619,10620],{"class":5249,"line":5346},[5247,10621,10622],{},"    Починаємо обережно.\n",[5247,10624,10625],{"class":5249,"line":5352},[5247,10626,10627],{},"  end note\n",[5247,10629,10630],{"class":5249,"line":5358},[5247,10631,5485],{},[5247,10633,10634],{"class":5249,"line":5364},[5247,10635,5278],{"emptyLinePlaceholder":5277},[5247,10637,10638],{"class":5249,"line":5369},[5247,10639,10640],{},"rectangle \"Main Training\\n(епохи 5-80)\" as main #MAIN_COLOR {\n",[5247,10642,10643],{"class":5249,"line":5375},[5247,10644,10593],{},[5247,10646,10647],{"class":5249,"line":5380},[5247,10648,10649],{},"    ⚡ Повна швидкість\n",[5247,10651,10652],{"class":5249,"line":5386},[5247,10653,10654],{},"    LR: 0.1 (фіксований)\n",[5247,10656,10657],{"class":5249,"line":5392},[5247,10658,5973],{},[5247,10660,10661],{"class":5249,"line":5398},[5247,10662,10663],{},"    Модель швидко навчається,\n",[5247,10665,10666],{"class":5249,"line":5404},[5247,10667,10668],{},"    ваги стабілізувалися.\n",[5247,10670,10671],{"class":5249,"line":5409},[5247,10672,10627],{},[5247,10674,10675],{"class":5249,"line":5414},[5247,10676,5485],{},[5247,10678,10679],{"class":5249,"line":5419},[5247,10680,5278],{"emptyLinePlaceholder":5277},[5247,10682,10683],{"class":5249,"line":5425},[5247,10684,10685],{},"rectangle \"Decay Phase\\n(епохи 80-120)\" as decay #DECAY_COLOR {\n",[5247,10687,10688],{"class":5249,"line":5430},[5247,10689,10593],{},[5247,10691,10692],{"class":5249,"line":5436},[5247,10693,10694],{},"    📉 Зменшення LR\n",[5247,10696,10697],{"class":5249,"line":5442},[5247,10698,10699],{},"    LR: 0.1 → 0.01 → 0.001\n",[5247,10701,10702],{"class":5249,"line":5448},[5247,10703,5973],{},[5247,10705,10706],{"class":5249,"line":5454},[5247,10707,10708],{},"    Fine-tuning біля мінімуму.\n",[5247,10710,10711],{"class":5249,"line":5460},[5247,10712,10627],{},[5247,10714,10715],{"class":5249,"line":5466},[5247,10716,5485],{},[5247,10718,10719],{"class":5249,"line":5472},[5247,10720,5278],{"emptyLinePlaceholder":5277},[5247,10722,10723],{"class":5249,"line":5477},[5247,10724,10725],{},"warmup -down-> main : Збільшення\\nдо цільового LR\n",[5247,10727,10728],{"class":5249,"line":5482},[5247,10729,10730],{},"main -down-> decay : Scheduler\\n(StepLR \u002F Cosine)\n",[5247,10732,10733],{"class":5249,"line":5488},[5247,10734,5278],{"emptyLinePlaceholder":5277},[5247,10736,10737],{"class":5249,"line":5493},[5247,10738,5542],{},[5191,10740,10741],{},[5195,10742,10743],{},"Математична реалізація (лінійний warm-up):",[5200,10745,10746],{},"\\eta_t = \\begin{cases}\n\\eta_{\\text{min}} + t \\cdot \\frac{\\eta_{\\text{max}} - \\eta_{\\text{min}}}{T_{\\text{warmup}}} & \\text{якщо } t \u003C T_{\\text{warmup}} \\\n\\eta_{\\text{max}} & \\text{інакше}\n\\end{cases}",[5191,10748,8018,10749,10752],{},[5200,10750],{"tex":10751,":inline":5203},"T_{\\text{warmup}}"," — кількість епох warm-up (зазвичай 5-10).",[5796,10754,10756,11715],{"execution-count":10755},"7",[5237,10757,10759],{"className":5812,"code":10758,"language":5814,"meta":5242,"style":5242},"# Реалізація Warm-up + CosineAnnealing вручну\nclass WarmupCosineScheduler:\n    def __init__(self, optimizer, warmup_epochs, total_epochs, eta_min=1e-6, warmup_start_lr=1e-5):\n        self.optimizer = optimizer\n        self.warmup_epochs = warmup_epochs\n        self.total_epochs = total_epochs\n        self.eta_min = eta_min\n        self.warmup_start_lr = warmup_start_lr\n        self.base_lr = optimizer.param_groups[0]['lr']\n        self.current_epoch = 0\n    \n    def step(self):\n        if self.current_epoch \u003C self.warmup_epochs:\n            # Лінійний warm-up\n            lr = self.warmup_start_lr + (self.base_lr - self.warmup_start_lr) * \\\n                 (self.current_epoch \u002F self.warmup_epochs)\n        else:\n            # Cosine annealing після warm-up\n            progress = (self.current_epoch - self.warmup_epochs) \u002F \\\n                      (self.total_epochs - self.warmup_epochs)\n            lr = self.eta_min + (self.base_lr - self.eta_min) * \\\n                 0.5 * (1 + np.cos(np.pi * progress))\n        \n        for param_group in self.optimizer.param_groups:\n            param_group['lr'] = lr\n        \n        self.current_epoch += 1\n        return lr\n\n# Симуляція\noptimizer = optim.SGD(model.parameters(), lr=0.1, momentum=0.9)\nscheduler = WarmupCosineScheduler(optimizer, warmup_epochs=5, total_epochs=100)\n\nlr_history_warmup = []\nfor epoch in range(100):\n    lr = scheduler.step()\n    lr_history_warmup.append(lr)\n\n# Візуалізація\nfig, axes = plt.subplots(1, 2, figsize=(16, 5))\n\n# Графік 1: Повний діапазон\nax = axes[0]\nax.plot(lr_history_warmup, linewidth=2.5, color='#f59e0b', label='Warm-up + Cosine')\nax.axvline(x=5, color='red', linestyle='--', alpha=0.5, linewidth=2, label='Кінець warm-up')\nax.fill_between([0, 5], 0, 0.15, alpha=0.2, color='orange', label='Warm-up фаза')\nax.set_xlabel('Epoch', fontsize=12)\nax.set_ylabel('Learning Rate', fontsize=12)\nax.set_title('Warm-up (5 епох) + Cosine Annealing', fontsize=14, fontweight='bold')\nax.legend(fontsize=11)\nax.grid(alpha=0.3)\n\n# Графік 2: Детальний перегляд warm-up фази\nax = axes[1]\nax.plot(range(10), lr_history_warmup[:10], 'o-', linewidth=2.5, markersize=8, \n        color='#f59e0b', label='Warm-up детально')\nax.set_xlabel('Epoch', fontsize=12)\nax.set_ylabel('Learning Rate', fontsize=12)\nax.set_title('Деталі Warm-up фази (епохи 0-9)', fontsize=14, fontweight='bold')\nax.legend(fontsize=11)\nax.grid(alpha=0.3)\n\nplt.tight_layout()\nplt.show()\n\nprint(\"📊 Warm-up + Cosine Scheduler:\")\nprint(f\"├─ Епоха 0 (старт warm-up): LR = {lr_history_warmup[0]:.8f}\")\nprint(f\"├─ Епоха 5 (кінець warm-up): LR = {lr_history_warmup[5]:.8f}\")\nprint(f\"├─ Епоха 50 (середина cosine): LR = {lr_history_warmup[50]:.8f}\")\nprint(f\"└─ Епоха 99 (фініш): LR = {lr_history_warmup[99]:.8f}\")\n",[5244,10760,10761,10766,10776,10824,10832,10839,10846,10853,10860,10875,10885,10889,10902,10917,10922,10942,10957,10964,10969,10984,10998,11016,11029,11034,11049,11059,11063,11073,11081,11085,11090,11110,11131,11135,11140,11156,11161,11166,11170,11174,11198,11202,11207,11215,11245,11299,11347,11363,11379,11404,11416,11428,11432,11437,11445,11485,11505,11521,11537,11562,11574,11586,11590,11594,11598,11602,11613,11640,11665,11690],{"__ignoreMap":5242},[5247,10762,10763],{"class":5249,"line":5250},[5247,10764,10765],{"class":5853},"# Реалізація Warm-up + CosineAnnealing вручну\n",[5247,10767,10768,10771,10774],{"class":5249,"line":5256},[5247,10769,10770],{"class":5859},"class",[5247,10772,10773],{"class":8317}," WarmupCosineScheduler",[5247,10775,6981],{"class":5825},[5247,10777,10778,10781,10784,10786,10789,10791,10794,10796,10799,10801,10804,10806,10808,10810,10812,10814,10817,10819,10822],{"class":5249,"line":5262},[5247,10779,10780],{"class":5859},"    def",[5247,10782,10783],{"class":5863}," __init__",[5247,10785,5867],{"class":5825},[5247,10787,10788],{"class":5870},"self",[5247,10790,5948],{"class":5825},[5247,10792,10793],{"class":5870},"optimizer",[5247,10795,5948],{"class":5825},[5247,10797,10798],{"class":5870},"warmup_epochs",[5247,10800,5948],{"class":5825},[5247,10802,10803],{"class":5870},"total_epochs",[5247,10805,5948],{"class":5825},[5247,10807,9053],{"class":5870},[5247,10809,6055],{"class":5825},[5247,10811,9058],{"class":5885},[5247,10813,5948],{"class":5825},[5247,10815,10816],{"class":5870},"warmup_start_lr",[5247,10818,6055],{"class":5825},[5247,10820,10821],{"class":5885},"1e-5",[5247,10823,5874],{"class":5825},[5247,10825,10826,10829],{"class":5249,"line":5268},[5247,10827,10828],{"class":5859},"        self",[5247,10830,10831],{"class":5825},".optimizer = optimizer\n",[5247,10833,10834,10836],{"class":5249,"line":5274},[5247,10835,10828],{"class":5859},[5247,10837,10838],{"class":5825},".warmup_epochs = warmup_epochs\n",[5247,10840,10841,10843],{"class":5249,"line":5281},[5247,10842,10828],{"class":5859},[5247,10844,10845],{"class":5825},".total_epochs = total_epochs\n",[5247,10847,10848,10850],{"class":5249,"line":5287},[5247,10849,10828],{"class":5859},[5247,10851,10852],{"class":5825},".eta_min = eta_min\n",[5247,10854,10855,10857],{"class":5249,"line":5293},[5247,10856,10828],{"class":5859},[5247,10858,10859],{"class":5825},".warmup_start_lr = warmup_start_lr\n",[5247,10861,10862,10864,10867,10869,10871,10873],{"class":5249,"line":5299},[5247,10863,10828],{"class":5859},[5247,10865,10866],{"class":5825},".base_lr = optimizer.param_groups[",[5247,10868,6216],{"class":5885},[5247,10870,7616],{"class":5825},[5247,10872,7619],{"class":6204},[5247,10874,6272],{"class":5825},[5247,10876,10877,10879,10882],{"class":5249,"line":5304},[5247,10878,10828],{"class":5859},[5247,10880,10881],{"class":5825},".current_epoch = ",[5247,10883,10884],{"class":5885},"0\n",[5247,10886,10887],{"class":5249,"line":5310},[5247,10888,5973],{"class":5825},[5247,10890,10891,10893,10896,10898,10900],{"class":5249,"line":5316},[5247,10892,10780],{"class":5859},[5247,10894,10895],{"class":5863}," step",[5247,10897,5867],{"class":5825},[5247,10899,10788],{"class":5870},[5247,10901,5874],{"class":5825},[5247,10903,10904,10906,10909,10912,10914],{"class":5249,"line":5322},[5247,10905,6584],{"class":5821},[5247,10907,10908],{"class":5859}," self",[5247,10910,10911],{"class":5825},".current_epoch \u003C ",[5247,10913,10788],{"class":5859},[5247,10915,10916],{"class":5825},".warmup_epochs:\n",[5247,10918,10919],{"class":5249,"line":5328},[5247,10920,10921],{"class":5853},"            # Лінійний warm-up\n",[5247,10923,10924,10927,10929,10932,10934,10937,10939],{"class":5249,"line":5334},[5247,10925,10926],{"class":5825},"            lr = ",[5247,10928,10788],{"class":5859},[5247,10930,10931],{"class":5825},".warmup_start_lr + (",[5247,10933,10788],{"class":5859},[5247,10935,10936],{"class":5825},".base_lr - ",[5247,10938,10788],{"class":5859},[5247,10940,10941],{"class":5825},".warmup_start_lr) * \\\n",[5247,10943,10944,10947,10949,10952,10954],{"class":5249,"line":5340},[5247,10945,10946],{"class":5825},"                 (",[5247,10948,10788],{"class":5859},[5247,10950,10951],{"class":5825},".current_epoch \u002F ",[5247,10953,10788],{"class":5859},[5247,10955,10956],{"class":5825},".warmup_epochs)\n",[5247,10958,10959,10962],{"class":5249,"line":5346},[5247,10960,10961],{"class":5821},"        else",[5247,10963,6981],{"class":5825},[5247,10965,10966],{"class":5249,"line":5352},[5247,10967,10968],{"class":5853},"            # Cosine annealing після warm-up\n",[5247,10970,10971,10974,10976,10979,10981],{"class":5249,"line":5358},[5247,10972,10973],{"class":5825},"            progress = (",[5247,10975,10788],{"class":5859},[5247,10977,10978],{"class":5825},".current_epoch - ",[5247,10980,10788],{"class":5859},[5247,10982,10983],{"class":5825},".warmup_epochs) \u002F \\\n",[5247,10985,10986,10989,10991,10994,10996],{"class":5249,"line":5364},[5247,10987,10988],{"class":5825},"                      (",[5247,10990,10788],{"class":5859},[5247,10992,10993],{"class":5825},".total_epochs - ",[5247,10995,10788],{"class":5859},[5247,10997,10956],{"class":5825},[5247,10999,11000,11002,11004,11007,11009,11011,11013],{"class":5249,"line":5369},[5247,11001,10926],{"class":5825},[5247,11003,10788],{"class":5859},[5247,11005,11006],{"class":5825},".eta_min + (",[5247,11008,10788],{"class":5859},[5247,11010,10936],{"class":5825},[5247,11012,10788],{"class":5859},[5247,11014,11015],{"class":5825},".eta_min) * \\\n",[5247,11017,11018,11021,11024,11026],{"class":5249,"line":5375},[5247,11019,11020],{"class":5885},"                 0.5",[5247,11022,11023],{"class":5825}," * (",[5247,11025,5808],{"class":5885},[5247,11027,11028],{"class":5825}," + np.cos(np.pi * progress))\n",[5247,11030,11031],{"class":5249,"line":5380},[5247,11032,11033],{"class":5825},"        \n",[5247,11035,11036,11039,11042,11044,11046],{"class":5249,"line":5386},[5247,11037,11038],{"class":5821},"        for",[5247,11040,11041],{"class":5825}," param_group ",[5247,11043,5984],{"class":5821},[5247,11045,10908],{"class":5859},[5247,11047,11048],{"class":5825},".optimizer.param_groups:\n",[5247,11050,11051,11054,11056],{"class":5249,"line":5392},[5247,11052,11053],{"class":5825},"            param_group[",[5247,11055,7619],{"class":6204},[5247,11057,11058],{"class":5825},"] = lr\n",[5247,11060,11061],{"class":5249,"line":5398},[5247,11062,11033],{"class":5825},[5247,11064,11065,11067,11070],{"class":5249,"line":5404},[5247,11066,10828],{"class":5859},[5247,11068,11069],{"class":5825},".current_epoch += ",[5247,11071,11072],{"class":5885},"1\n",[5247,11074,11075,11078],{"class":5249,"line":5409},[5247,11076,11077],{"class":5821},"        return",[5247,11079,11080],{"class":5825}," lr\n",[5247,11082,11083],{"class":5249,"line":5414},[5247,11084,5278],{"emptyLinePlaceholder":5277},[5247,11086,11087],{"class":5249,"line":5419},[5247,11088,11089],{"class":5853},"# Симуляція\n",[5247,11091,11092,11094,11096,11098,11100,11102,11104,11106,11108],{"class":5249,"line":5425},[5247,11093,7515],{"class":5825},[5247,11095,5951],{"class":5870},[5247,11097,6055],{"class":5825},[5247,11099,6058],{"class":5885},[5247,11101,5948],{"class":5825},[5247,11103,7526],{"class":5870},[5247,11105,6055],{"class":5825},[5247,11107,7531],{"class":5885},[5247,11109,5924],{"class":5825},[5247,11111,11112,11115,11117,11119,11121,11123,11125,11127,11129],{"class":5249,"line":5430},[5247,11113,11114],{"class":5825},"scheduler = WarmupCosineScheduler(optimizer, ",[5247,11116,10798],{"class":5870},[5247,11118,6055],{"class":5825},[5247,11120,6147],{"class":5885},[5247,11122,5948],{"class":5825},[5247,11124,10803],{"class":5870},[5247,11126,6055],{"class":5825},[5247,11128,9048],{"class":5885},[5247,11130,5924],{"class":5825},[5247,11132,11133],{"class":5249,"line":5436},[5247,11134,5278],{"emptyLinePlaceholder":5277},[5247,11136,11137],{"class":5249,"line":5442},[5247,11138,11139],{"class":5825},"lr_history_warmup = []\n",[5247,11141,11142,11144,11146,11148,11150,11152,11154],{"class":5249,"line":5448},[5247,11143,6281],{"class":5821},[5247,11145,7599],{"class":5825},[5247,11147,5984],{"class":5821},[5247,11149,5987],{"class":5863},[5247,11151,5867],{"class":5825},[5247,11153,9048],{"class":5885},[5247,11155,5874],{"class":5825},[5247,11157,11158],{"class":5249,"line":5454},[5247,11159,11160],{"class":5825},"    lr = scheduler.step()\n",[5247,11162,11163],{"class":5249,"line":5460},[5247,11164,11165],{"class":5825},"    lr_history_warmup.append(lr)\n",[5247,11167,11168],{"class":5249,"line":5466},[5247,11169,5278],{"emptyLinePlaceholder":5277},[5247,11171,11172],{"class":5249,"line":5472},[5247,11173,6120],{"class":5853},[5247,11175,11176,11178,11180,11182,11184,11186,11188,11190,11192,11194,11196],{"class":5249,"line":5477},[5247,11177,6125],{"class":5825},[5247,11179,5808],{"class":5885},[5247,11181,5948],{"class":5825},[5247,11183,6264],{"class":5885},[5247,11185,5948],{"class":5825},[5247,11187,6136],{"class":5870},[5247,11189,6139],{"class":5825},[5247,11191,9130],{"class":5885},[5247,11193,5948],{"class":5825},[5247,11195,6147],{"class":5885},[5247,11197,6150],{"class":5825},[5247,11199,11200],{"class":5249,"line":5482},[5247,11201,5278],{"emptyLinePlaceholder":5277},[5247,11203,11204],{"class":5249,"line":5488},[5247,11205,11206],{"class":5853},"# Графік 1: Повний діапазон\n",[5247,11208,11209,11211,11213],{"class":5249,"line":5493},[5247,11210,9150],{"class":5825},[5247,11212,6216],{"class":5885},[5247,11214,6272],{"class":5825},[5247,11216,11217,11220,11222,11224,11226,11228,11230,11232,11234,11236,11238,11240,11243],{"class":5249,"line":5499},[5247,11218,11219],{"class":5825},"ax.plot(lr_history_warmup, ",[5247,11221,6307],{"class":5870},[5247,11223,6055],{"class":5825},[5247,11225,6428],{"class":5885},[5247,11227,5948],{"class":5825},[5247,11229,6418],{"class":5870},[5247,11231,6055],{"class":5825},[5247,11233,8632],{"class":6204},[5247,11235,5948],{"class":5825},[5247,11237,6327],{"class":5870},[5247,11239,6055],{"class":5825},[5247,11241,11242],{"class":6204},"'Warm-up + Cosine'",[5247,11244,5924],{"class":5825},[5247,11246,11247,11250,11252,11254,11256,11258,11260,11262,11264,11266,11268,11270,11272,11274,11276,11278,11280,11282,11284,11286,11288,11290,11292,11294,11297],{"class":5249,"line":5505},[5247,11248,11249],{"class":5825},"ax.axvline(",[5247,11251,8223],{"class":5870},[5247,11253,6055],{"class":5825},[5247,11255,6147],{"class":5885},[5247,11257,5948],{"class":5825},[5247,11259,6418],{"class":5870},[5247,11261,6055],{"class":5825},[5247,11263,8233],{"class":6204},[5247,11265,5948],{"class":5825},[5247,11267,8238],{"class":5870},[5247,11269,6055],{"class":5825},[5247,11271,8243],{"class":6204},[5247,11273,5948],{"class":5825},[5247,11275,6317],{"class":5870},[5247,11277,6055],{"class":5825},[5247,11279,6080],{"class":5885},[5247,11281,5948],{"class":5825},[5247,11283,6307],{"class":5870},[5247,11285,6055],{"class":5825},[5247,11287,6264],{"class":5885},[5247,11289,5948],{"class":5825},[5247,11291,6327],{"class":5870},[5247,11293,6055],{"class":5825},[5247,11295,11296],{"class":6204},"'Кінець warm-up'",[5247,11298,5924],{"class":5825},[5247,11300,11301,11304,11306,11308,11310,11312,11314,11316,11318,11320,11322,11324,11327,11329,11331,11333,11336,11338,11340,11342,11345],{"class":5249,"line":5510},[5247,11302,11303],{"class":5825},"ax.fill_between([",[5247,11305,6216],{"class":5885},[5247,11307,5948],{"class":5825},[5247,11309,6147],{"class":5885},[5247,11311,6488],{"class":5825},[5247,11313,6216],{"class":5885},[5247,11315,5948],{"class":5825},[5247,11317,8269],{"class":5885},[5247,11319,5948],{"class":5825},[5247,11321,6317],{"class":5870},[5247,11323,6055],{"class":5825},[5247,11325,11326],{"class":5885},"0.2",[5247,11328,5948],{"class":5825},[5247,11330,6418],{"class":5870},[5247,11332,6055],{"class":5825},[5247,11334,11335],{"class":6204},"'orange'",[5247,11337,5948],{"class":5825},[5247,11339,6327],{"class":5870},[5247,11341,6055],{"class":5825},[5247,11343,11344],{"class":6204},"'Warm-up фаза'",[5247,11346,5924],{"class":5825},[5247,11348,11349,11351,11353,11355,11357,11359,11361],{"class":5249,"line":5516},[5247,11350,9189],{"class":5825},[5247,11352,7712],{"class":6204},[5247,11354,5948],{"class":5825},[5247,11356,6653],{"class":5870},[5247,11358,6055],{"class":5825},[5247,11360,6500],{"class":5885},[5247,11362,5924],{"class":5825},[5247,11364,11365,11367,11369,11371,11373,11375,11377],{"class":5249,"line":5522},[5247,11366,9206],{"class":5825},[5247,11368,7730],{"class":6204},[5247,11370,5948],{"class":5825},[5247,11372,6653],{"class":5870},[5247,11374,6055],{"class":5825},[5247,11376,6500],{"class":5885},[5247,11378,5924],{"class":5825},[5247,11380,11381,11383,11386,11388,11390,11392,11394,11396,11398,11400,11402],{"class":5249,"line":5528},[5247,11382,9223],{"class":5825},[5247,11384,11385],{"class":6204},"'Warm-up (5 епох) + Cosine Annealing'",[5247,11387,5948],{"class":5825},[5247,11389,6653],{"class":5870},[5247,11391,6055],{"class":5825},[5247,11393,6565],{"class":5885},[5247,11395,5948],{"class":5825},[5247,11397,6721],{"class":5870},[5247,11399,6055],{"class":5825},[5247,11401,6726],{"class":6204},[5247,11403,5924],{"class":5825},[5247,11405,11406,11408,11410,11412,11414],{"class":5249,"line":5534},[5247,11407,9262],{"class":5825},[5247,11409,6653],{"class":5870},[5247,11411,6055],{"class":5825},[5247,11413,7805],{"class":5885},[5247,11415,5924],{"class":5825},[5247,11417,11418,11420,11422,11424,11426],{"class":5249,"line":5539},[5247,11419,9249],{"class":5825},[5247,11421,6317],{"class":5870},[5247,11423,6055],{"class":5825},[5247,11425,6322],{"class":5885},[5247,11427,5924],{"class":5825},[5247,11429,11430],{"class":5249,"line":6401},[5247,11431,5278],{"emptyLinePlaceholder":5277},[5247,11433,11434],{"class":5249,"line":6407},[5247,11435,11436],{"class":5853},"# Графік 2: Детальний перегляд warm-up фази\n",[5247,11438,11439,11441,11443],{"class":5249,"line":6434},[5247,11440,9150],{"class":5825},[5247,11442,5808],{"class":5885},[5247,11444,6272],{"class":5825},[5247,11446,11447,11450,11453,11455,11457,11460,11462,11464,11466,11468,11470,11472,11474,11476,11478,11480,11483],{"class":5249,"line":6464},[5247,11448,11449],{"class":5825},"ax.plot(",[5247,11451,11452],{"class":5863},"range",[5247,11454,5867],{"class":5825},[5247,11456,6555],{"class":5885},[5247,11458,11459],{"class":5825},"), lr_history_warmup[:",[5247,11461,6555],{"class":5885},[5247,11463,6488],{"class":5825},[5247,11465,6413],{"class":6204},[5247,11467,5948],{"class":5825},[5247,11469,6307],{"class":5870},[5247,11471,6055],{"class":5825},[5247,11473,6428],{"class":5885},[5247,11475,5948],{"class":5825},[5247,11477,6364],{"class":5870},[5247,11479,6055],{"class":5825},[5247,11481,11482],{"class":5885},"8",[5247,11484,6431],{"class":5825},[5247,11486,11487,11490,11492,11494,11496,11498,11500,11503],{"class":5249,"line":6469},[5247,11488,11489],{"class":5870},"        color",[5247,11491,6055],{"class":5825},[5247,11493,8632],{"class":6204},[5247,11495,5948],{"class":5825},[5247,11497,6327],{"class":5870},[5247,11499,6055],{"class":5825},[5247,11501,11502],{"class":6204},"'Warm-up детально'",[5247,11504,5924],{"class":5825},[5247,11506,11507,11509,11511,11513,11515,11517,11519],{"class":5249,"line":6475},[5247,11508,9189],{"class":5825},[5247,11510,7712],{"class":6204},[5247,11512,5948],{"class":5825},[5247,11514,6653],{"class":5870},[5247,11516,6055],{"class":5825},[5247,11518,6500],{"class":5885},[5247,11520,5924],{"class":5825},[5247,11522,11523,11525,11527,11529,11531,11533,11535],{"class":5249,"line":6523},[5247,11524,9206],{"class":5825},[5247,11526,7730],{"class":6204},[5247,11528,5948],{"class":5825},[5247,11530,6653],{"class":5870},[5247,11532,6055],{"class":5825},[5247,11534,6500],{"class":5885},[5247,11536,5924],{"class":5825},[5247,11538,11539,11541,11544,11546,11548,11550,11552,11554,11556,11558,11560],{"class":5249,"line":6528},[5247,11540,9223],{"class":5825},[5247,11542,11543],{"class":6204},"'Деталі Warm-up фази (епохи 0-9)'",[5247,11545,5948],{"class":5825},[5247,11547,6653],{"class":5870},[5247,11549,6055],{"class":5825},[5247,11551,6565],{"class":5885},[5247,11553,5948],{"class":5825},[5247,11555,6721],{"class":5870},[5247,11557,6055],{"class":5825},[5247,11559,6726],{"class":6204},[5247,11561,5924],{"class":5825},[5247,11563,11564,11566,11568,11570,11572],{"class":5249,"line":6534},[5247,11565,9262],{"class":5825},[5247,11567,6653],{"class":5870},[5247,11569,6055],{"class":5825},[5247,11571,7805],{"class":5885},[5247,11573,5924],{"class":5825},[5247,11575,11576,11578,11580,11582,11584],{"class":5249,"line":6581},[5247,11577,9249],{"class":5825},[5247,11579,6317],{"class":5870},[5247,11581,6055],{"class":5825},[5247,11583,6322],{"class":5885},[5247,11585,5924],{"class":5825},[5247,11587,11588],{"class":5249,"line":6595},[5247,11589,5278],{"emptyLinePlaceholder":5277},[5247,11591,11592],{"class":5249,"line":6626},[5247,11593,6782],{"class":5825},[5247,11595,11596],{"class":5249,"line":6663},[5247,11597,6788],{"class":5825},[5247,11599,11600],{"class":5249,"line":6668},[5247,11601,5278],{"emptyLinePlaceholder":5277},[5247,11603,11604,11606,11608,11611],{"class":5249,"line":6687},[5247,11605,6805],{"class":5863},[5247,11607,5867],{"class":5825},[5247,11609,11610],{"class":6204},"\"📊 Warm-up + Cosine Scheduler:\"",[5247,11612,5924],{"class":5825},[5247,11614,11615,11617,11619,11621,11624,11626,11629,11631,11633,11636,11638],{"class":5249,"line":6706},[5247,11616,6805],{"class":5863},[5247,11618,5867],{"class":5825},[5247,11620,6601],{"class":5859},[5247,11622,11623],{"class":6204},"\"├─ Епоха 0 (старт warm-up): LR = ",[5247,11625,6607],{"class":5859},[5247,11627,11628],{"class":5825},"lr_history_warmup[",[5247,11630,6216],{"class":5885},[5247,11632,7851],{"class":5825},[5247,11634,11635],{"class":5859},":.8f}",[5247,11637,6817],{"class":6204},[5247,11639,5924],{"class":5825},[5247,11641,11642,11644,11646,11648,11651,11653,11655,11657,11659,11661,11663],{"class":5249,"line":6731},[5247,11643,6805],{"class":5863},[5247,11645,5867],{"class":5825},[5247,11647,6601],{"class":5859},[5247,11649,11650],{"class":6204},"\"├─ Епоха 5 (кінець warm-up): LR = ",[5247,11652,6607],{"class":5859},[5247,11654,11628],{"class":5825},[5247,11656,6147],{"class":5885},[5247,11658,7851],{"class":5825},[5247,11660,11635],{"class":5859},[5247,11662,6817],{"class":6204},[5247,11664,5924],{"class":5825},[5247,11666,11667,11669,11671,11673,11676,11678,11680,11682,11684,11686,11688],{"class":5249,"line":6745},[5247,11668,6805],{"class":5863},[5247,11670,5867],{"class":5825},[5247,11672,6601],{"class":5859},[5247,11674,11675],{"class":6204},"\"├─ Епоха 50 (середина cosine): LR = ",[5247,11677,6607],{"class":5859},[5247,11679,11628],{"class":5825},[5247,11681,8828],{"class":5885},[5247,11683,7851],{"class":5825},[5247,11685,11635],{"class":5859},[5247,11687,6817],{"class":6204},[5247,11689,5924],{"class":5825},[5247,11691,11692,11694,11696,11698,11701,11703,11705,11707,11709,11711,11713],{"class":5249,"line":6759},[5247,11693,6805],{"class":5863},[5247,11695,5867],{"class":5825},[5247,11697,6601],{"class":5859},[5247,11699,11700],{"class":6204},"\"└─ Епоха 99 (фініш): LR = ",[5247,11702,6607],{"class":5859},[5247,11704,11628],{"class":5825},[5247,11706,8880],{"class":5885},[5247,11708,7851],{"class":5825},[5247,11710,11635],{"class":5859},[5247,11712,6817],{"class":6204},[5247,11714,5924],{"class":5825},[7107,11716,11717,11724,11729],{"v-slot:output":5242},[5191,11718,11719],{},[7112,11720],{"alt":11721,"className":11722,"src":11723},"Warm-up: поступове збільшення LR на початку, потім cosine decay",[7116],"\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling\u002F07.png",[5191,11725,7120,11726],{},[5195,11727,11728],{},"Warm-up + Cosine Scheduler:",[5625,11730,11731,11734,11737,11740],{},[5628,11732,11733],{},"Епоха 0 (старт warm-up): LR = 0.00001000",[5628,11735,11736],{},"Епоха 5 (кінець warm-up): LR = 0.10000000",[5628,11738,11739],{},"Епоха 50 (середина cosine): LR = 0.05000314",[5628,11741,11742],{},"Епоха 99 (фініш): LR = 0.00000100",[5191,11744,11745],{},[5195,11746,11747],{},"Коли використовувати Warm-up:",[5209,11749,11750,11761,11765],{},[5212,11751,11753,11756],{"icon":2865,"title":11752},"🤖 Великі batch sizes (>256)",[5191,11754,11755],{},"Великі батчі дають менш шумні градієнти, що дозволяє використовувати великі LR. Але на початку навчання великий LR може спричинити нестабільність. Warm-up вирішує це.",[5191,11757,11758,11760],{},[5195,11759,7380],{}," BERT тренується з batch_size=256, використовує 10k ітерацій warm-up.",[5212,11762,11764],{"icon":943,"title":11763},"🏗️ Дуже глибокі мережі (ResNet-101+)","Градієнти у дуже глибоких мережах можуть бути нестабільними на початку, навіть з BatchNorm та skip connections.",[5212,11766,11769],{"icon":11767,"title":11768},"i-lucide-repeat","🔄 Transfer Learning","Коли fine-tune pretrained модель, початкові епохи критичні — можна зруйнувати претреновані ваги занадто великим LR.",[9553,11771,11772,11782],{},[5191,11773,11774,11777,11778,11781],{},[5195,11775,11776],{},"PyTorch не має вбудованого Warm-up scheduler",", але його легко реалізувати самостійно або використовувати бібліотеку ",[5244,11779,11780],{},"transformers"," від HuggingFace:",[5237,11783,11785],{"className":5812,"code":11784,"language":5814,"meta":5242,"style":5242},"from transformers import get_linear_schedule_with_warmup\n\nscheduler = get_linear_schedule_with_warmup(\n    optimizer,\n    num_warmup_steps=500,      # Перші 500 ітерацій — warm-up\n    num_training_steps=10000   # Загальна кількість ітерацій\n)\n",[5244,11786,11787,11800,11804,11809,11813,11828,11841],{"__ignoreMap":5242},[5247,11788,11789,11792,11795,11797],{"class":5249,"line":5250},[5247,11790,11791],{"class":5821},"from",[5247,11793,11794],{"class":5825}," transformers ",[5247,11796,5822],{"class":5821},[5247,11798,11799],{"class":5825}," get_linear_schedule_with_warmup\n",[5247,11801,11802],{"class":5249,"line":5256},[5247,11803,5278],{"emptyLinePlaceholder":5277},[5247,11805,11806],{"class":5249,"line":5262},[5247,11807,11808],{"class":5825},"scheduler = get_linear_schedule_with_warmup(\n",[5247,11810,11811],{"class":5249,"line":5268},[5247,11812,9653],{"class":5825},[5247,11814,11815,11818,11820,11823,11825],{"class":5249,"line":5274},[5247,11816,11817],{"class":5870},"    num_warmup_steps",[5247,11819,6055],{"class":5825},[5247,11821,11822],{"class":5885},"500",[5247,11824,9666],{"class":5825},[5247,11826,11827],{"class":5853},"# Перші 500 ітерацій — warm-up\n",[5247,11829,11830,11833,11835,11838],{"class":5249,"line":5281},[5247,11831,11832],{"class":5870},"    num_training_steps",[5247,11834,6055],{"class":5825},[5247,11836,11837],{"class":5885},"10000",[5247,11839,11840],{"class":5853},"   # Загальна кількість ітерацій\n",[5247,11842,11843],{"class":5249,"line":5287},[5247,11844,5924],{"class":5825},[5712,11846],{},[5544,11848,11850],{"id":11849},"sgdr-warm-restarts-перезапуск-warm","SGDR — Warm Restarts (Перезапуск Warm)",[5191,11852,11853,11855,11856,11859],{},[5195,11854,7338],{}," Періодично ",[5195,11857,11858],{},"скидати LR до початкового значення"," (restart), замість монотонного зменшення. Це дозволяє моделі \"виштовхнутися\" з локальних мінімумів та знайти кращі розв'язки.",[5191,11861,11862,11865],{},[5195,11863,11864],{},"Метафора:"," Уявіть кулю, що котиться долиною до ямки (локальний мінімум). Якщо періодично \"підкидати\" кулю вгору (restart LR), вона може перекотитися через гірку та знайти глибшу ямку (кращий глобальний мінімум).",[5191,11867,11868],{},[5195,11869,11870],{},"Математика (Cosine Annealing with Warm Restarts):",[5200,11872],{"tex":11873},"\\eta_t = \\eta_{\\text{min}} + \\frac{1}{2}(\\eta_{\\text{max}} - \\eta_{\\text{min}})\\left(1 + \\cos\\left(\\frac{T_{\\text{cur}}}{T_i} \\pi\\right)\\right)",[5191,11875,5733],{},[5625,11877,11878,11884],{},[5628,11879,11880,11883],{},[5200,11881],{"tex":11882,":inline":5203},"T_{\\text{cur}}"," — кількість епох з моменту останнього restart",[5628,11885,11886,11889],{},[5200,11887],{"tex":11888,":inline":5203},"T_i"," — кількість епох до наступного restart",[5191,11891,11892,11893],{},"Кожен restart подвоює період: ",[5200,11894],{"tex":11895,":inline":5203},"T_i = T_0, 2T_0, 4T_0, 8T_0, \\ldots",[5796,11897,11898,12433],{"execution-count":11482},[5237,11899,11901],{"className":5812,"code":11900,"language":5814,"meta":5242,"style":5242},"# PyTorch CosineAnnealingWarmRestarts\noptimizer = optim.SGD(model.parameters(), lr=0.1, momentum=0.9)\nscheduler = optim.lr_scheduler.CosineAnnealingWarmRestarts(\n    optimizer,\n    T_0=10,      # Перший restart через 10 епох\n    T_mult=2,    # Кожен наступний період подвоюється\n    eta_min=1e-6\n)\n\nlr_history_sgdr = []\nfor epoch in range(150):  # Довше навчання для демонстрації\n    lr_history_sgdr.append(optimizer.param_groups[0]['lr'])\n    optimizer.step()\n    scheduler.step()\n\n# Візуалізація\nplt.figure(figsize=(14, 6))\nplt.plot(lr_history_sgdr, linewidth=2.5, color='#8b5cf6', label='SGDR (T_0=10, T_mult=2)')\n\n# Позначимо restart точки\nrestart_epochs = [10, 30, 70]  # 10, 10+20, 10+20+40\nfor restart_epoch in restart_epochs:\n    if restart_epoch \u003C len(lr_history_sgdr):\n        plt.axvline(x=restart_epoch, color='red', linestyle='--', alpha=0.5, linewidth=2)\n        plt.text(restart_epoch, 0.12, f'Restart', ha='center', fontsize=10, rotation=90,\n                bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.5))\n\nplt.xlabel('Epoch', fontsize=12)\nplt.ylabel('Learning Rate', fontsize=12)\nplt.title('SGDR (Warm Restarts) — періодичні стрибки LR', fontsize=14, fontweight='bold')\nplt.grid(alpha=0.3)\nplt.legend(fontsize=11)\nplt.tight_layout()\nplt.show()\n\nprint(\"📊 SGDR Warm Restarts:\")\nprint(f\"├─ Перший період (епохи 0-9): cosine decay\")\nprint(f\"├─ Restart на епосі 10: LR → 0.1\")\nprint(f\"├─ Другий період (епохи 10-29, довжина 20): cosine decay\")\nprint(f\"├─ Restart на епосі 30: LR → 0.1\")\nprint(f\"└─ Третій період (епохи 30-69, довжина 40): cosine decay\")\n",[5244,11902,11903,11908,11928,11933,11937,11951,11966,11976,11980,11984,11989,12010,12023,12027,12031,12035,12039,12055,12085,12089,12094,12116,12128,12140,12182,12225,12260,12264,12280,12296,12321,12333,12345,12349,12353,12357,12368,12381,12394,12407,12420],{"__ignoreMap":5242},[5247,11904,11905],{"class":5249,"line":5250},[5247,11906,11907],{"class":5853},"# PyTorch CosineAnnealingWarmRestarts\n",[5247,11909,11910,11912,11914,11916,11918,11920,11922,11924,11926],{"class":5249,"line":5256},[5247,11911,7515],{"class":5825},[5247,11913,5951],{"class":5870},[5247,11915,6055],{"class":5825},[5247,11917,6058],{"class":5885},[5247,11919,5948],{"class":5825},[5247,11921,7526],{"class":5870},[5247,11923,6055],{"class":5825},[5247,11925,7531],{"class":5885},[5247,11927,5924],{"class":5825},[5247,11929,11930],{"class":5249,"line":5262},[5247,11931,11932],{"class":5825},"scheduler = optim.lr_scheduler.CosineAnnealingWarmRestarts(\n",[5247,11934,11935],{"class":5249,"line":5268},[5247,11936,9653],{"class":5825},[5247,11938,11939,11942,11944,11946,11948],{"class":5249,"line":5274},[5247,11940,11941],{"class":5870},"    T_0",[5247,11943,6055],{"class":5825},[5247,11945,6555],{"class":5885},[5247,11947,9666],{"class":5825},[5247,11949,11950],{"class":5853},"# Перший restart через 10 епох\n",[5247,11952,11953,11956,11958,11960,11963],{"class":5249,"line":5281},[5247,11954,11955],{"class":5870},"    T_mult",[5247,11957,6055],{"class":5825},[5247,11959,6264],{"class":5885},[5247,11961,11962],{"class":5825},",    ",[5247,11964,11965],{"class":5853},"# Кожен наступний період подвоюється\n",[5247,11967,11968,11971,11973],{"class":5249,"line":5287},[5247,11969,11970],{"class":5870},"    eta_min",[5247,11972,6055],{"class":5825},[5247,11974,11975],{"class":5885},"1e-6\n",[5247,11977,11978],{"class":5249,"line":5293},[5247,11979,5924],{"class":5825},[5247,11981,11982],{"class":5249,"line":5299},[5247,11983,5278],{"emptyLinePlaceholder":5277},[5247,11985,11986],{"class":5249,"line":5304},[5247,11987,11988],{"class":5825},"lr_history_sgdr = []\n",[5247,11990,11991,11993,11995,11997,11999,12001,12004,12007],{"class":5249,"line":5310},[5247,11992,6281],{"class":5821},[5247,11994,7599],{"class":5825},[5247,11996,5984],{"class":5821},[5247,11998,5987],{"class":5863},[5247,12000,5867],{"class":5825},[5247,12002,12003],{"class":5885},"150",[5247,12005,12006],{"class":5825},"):  ",[5247,12008,12009],{"class":5853},"# Довше навчання для демонстрації\n",[5247,12011,12012,12015,12017,12019,12021],{"class":5249,"line":5316},[5247,12013,12014],{"class":5825},"    lr_history_sgdr.append(optimizer.param_groups[",[5247,12016,6216],{"class":5885},[5247,12018,7616],{"class":5825},[5247,12020,7619],{"class":6204},[5247,12022,6267],{"class":5825},[5247,12024,12025],{"class":5249,"line":5322},[5247,12026,7635],{"class":5825},[5247,12028,12029],{"class":5249,"line":5328},[5247,12030,7649],{"class":5825},[5247,12032,12033],{"class":5249,"line":5334},[5247,12034,5278],{"emptyLinePlaceholder":5277},[5247,12036,12037],{"class":5249,"line":5340},[5247,12038,6120],{"class":5853},[5247,12040,12041,12043,12045,12047,12049,12051,12053],{"class":5249,"line":5346},[5247,12042,7662],{"class":5825},[5247,12044,6136],{"class":5870},[5247,12046,6139],{"class":5825},[5247,12048,6565],{"class":5885},[5247,12050,5948],{"class":5825},[5247,12052,6171],{"class":5885},[5247,12054,6150],{"class":5825},[5247,12056,12057,12060,12062,12064,12066,12068,12070,12072,12074,12076,12078,12080,12083],{"class":5249,"line":5352},[5247,12058,12059],{"class":5825},"plt.plot(lr_history_sgdr, ",[5247,12061,6307],{"class":5870},[5247,12063,6055],{"class":5825},[5247,12065,6428],{"class":5885},[5247,12067,5948],{"class":5825},[5247,12069,6418],{"class":5870},[5247,12071,6055],{"class":5825},[5247,12073,8171],{"class":6204},[5247,12075,5948],{"class":5825},[5247,12077,6327],{"class":5870},[5247,12079,6055],{"class":5825},[5247,12081,12082],{"class":6204},"'SGDR (T_0=10, T_mult=2)'",[5247,12084,5924],{"class":5825},[5247,12086,12087],{"class":5249,"line":5358},[5247,12088,5278],{"emptyLinePlaceholder":5277},[5247,12090,12091],{"class":5249,"line":5364},[5247,12092,12093],{"class":5853},"# Позначимо restart точки\n",[5247,12095,12096,12099,12101,12103,12105,12107,12110,12113],{"class":5249,"line":5369},[5247,12097,12098],{"class":5825},"restart_epochs = [",[5247,12100,6555],{"class":5885},[5247,12102,5948],{"class":5825},[5247,12104,7555],{"class":5885},[5247,12106,5948],{"class":5825},[5247,12108,12109],{"class":5885},"70",[5247,12111,12112],{"class":5825},"]  ",[5247,12114,12115],{"class":5853},"# 10, 10+20, 10+20+40\n",[5247,12117,12118,12120,12123,12125],{"class":5249,"line":5375},[5247,12119,6281],{"class":5821},[5247,12121,12122],{"class":5825}," restart_epoch ",[5247,12124,5984],{"class":5821},[5247,12126,12127],{"class":5825}," restart_epochs:\n",[5247,12129,12130,12132,12135,12137],{"class":5249,"line":5380},[5247,12131,10248],{"class":5821},[5247,12133,12134],{"class":5825}," restart_epoch \u003C ",[5247,12136,6570],{"class":5863},[5247,12138,12139],{"class":5825},"(lr_history_sgdr):\n",[5247,12141,12142,12145,12147,12150,12152,12154,12156,12158,12160,12162,12164,12166,12168,12170,12172,12174,12176,12178,12180],{"class":5249,"line":5386},[5247,12143,12144],{"class":5825},"        plt.axvline(",[5247,12146,8223],{"class":5870},[5247,12148,12149],{"class":5825},"=restart_epoch, ",[5247,12151,6418],{"class":5870},[5247,12153,6055],{"class":5825},[5247,12155,8233],{"class":6204},[5247,12157,5948],{"class":5825},[5247,12159,8238],{"class":5870},[5247,12161,6055],{"class":5825},[5247,12163,8243],{"class":6204},[5247,12165,5948],{"class":5825},[5247,12167,6317],{"class":5870},[5247,12169,6055],{"class":5825},[5247,12171,6080],{"class":5885},[5247,12173,5948],{"class":5825},[5247,12175,6307],{"class":5870},[5247,12177,6055],{"class":5825},[5247,12179,6264],{"class":5885},[5247,12181,5924],{"class":5825},[5247,12183,12184,12187,12190,12192,12194,12197,12199,12201,12203,12205,12207,12209,12211,12213,12215,12218,12220,12222],{"class":5249,"line":5392},[5247,12185,12186],{"class":5825},"        plt.text(restart_epoch, ",[5247,12188,12189],{"class":5885},"0.12",[5247,12191,5948],{"class":5825},[5247,12193,6601],{"class":5859},[5247,12195,12196],{"class":6204},"'Restart'",[5247,12198,5948],{"class":5825},[5247,12200,8292],{"class":5870},[5247,12202,6055],{"class":5825},[5247,12204,8297],{"class":6204},[5247,12206,5948],{"class":5825},[5247,12208,6653],{"class":5870},[5247,12210,6055],{"class":5825},[5247,12212,6555],{"class":5885},[5247,12214,5948],{"class":5825},[5247,12216,12217],{"class":5870},"rotation",[5247,12219,6055],{"class":5825},[5247,12221,7927],{"class":5885},[5247,12223,12224],{"class":5825},",\n",[5247,12226,12227,12230,12232,12234,12236,12238,12240,12242,12244,12246,12248,12250,12252,12254,12256,12258],{"class":5249,"line":5398},[5247,12228,12229],{"class":5870},"                bbox",[5247,12231,6055],{"class":5825},[5247,12233,8318],{"class":8317},[5247,12235,5867],{"class":5825},[5247,12237,8323],{"class":5870},[5247,12239,6055],{"class":5825},[5247,12241,8328],{"class":6204},[5247,12243,5948],{"class":5825},[5247,12245,8333],{"class":5870},[5247,12247,6055],{"class":5825},[5247,12249,8338],{"class":6204},[5247,12251,5948],{"class":5825},[5247,12253,6317],{"class":5870},[5247,12255,6055],{"class":5825},[5247,12257,6080],{"class":5885},[5247,12259,6150],{"class":5825},[5247,12261,12262],{"class":5249,"line":5404},[5247,12263,5278],{"emptyLinePlaceholder":5277},[5247,12265,12266,12268,12270,12272,12274,12276,12278],{"class":5249,"line":5409},[5247,12267,7709],{"class":5825},[5247,12269,7712],{"class":6204},[5247,12271,5948],{"class":5825},[5247,12273,6653],{"class":5870},[5247,12275,6055],{"class":5825},[5247,12277,6500],{"class":5885},[5247,12279,5924],{"class":5825},[5247,12281,12282,12284,12286,12288,12290,12292,12294],{"class":5249,"line":5414},[5247,12283,7727],{"class":5825},[5247,12285,7730],{"class":6204},[5247,12287,5948],{"class":5825},[5247,12289,6653],{"class":5870},[5247,12291,6055],{"class":5825},[5247,12293,6500],{"class":5885},[5247,12295,5924],{"class":5825},[5247,12297,12298,12300,12303,12305,12307,12309,12311,12313,12315,12317,12319],{"class":5249,"line":5419},[5247,12299,7745],{"class":5825},[5247,12301,12302],{"class":6204},"'SGDR (Warm Restarts) — періодичні стрибки LR'",[5247,12304,5948],{"class":5825},[5247,12306,6653],{"class":5870},[5247,12308,6055],{"class":5825},[5247,12310,6565],{"class":5885},[5247,12312,5948],{"class":5825},[5247,12314,6721],{"class":5870},[5247,12316,6055],{"class":5825},[5247,12318,6726],{"class":6204},[5247,12320,5924],{"class":5825},[5247,12322,12323,12325,12327,12329,12331],{"class":5249,"line":5425},[5247,12324,7785],{"class":5825},[5247,12326,6317],{"class":5870},[5247,12328,6055],{"class":5825},[5247,12330,6322],{"class":5885},[5247,12332,5924],{"class":5825},[5247,12334,12335,12337,12339,12341,12343],{"class":5249,"line":5430},[5247,12336,7798],{"class":5825},[5247,12338,6653],{"class":5870},[5247,12340,6055],{"class":5825},[5247,12342,7805],{"class":5885},[5247,12344,5924],{"class":5825},[5247,12346,12347],{"class":5249,"line":5436},[5247,12348,6782],{"class":5825},[5247,12350,12351],{"class":5249,"line":5442},[5247,12352,6788],{"class":5825},[5247,12354,12355],{"class":5249,"line":5448},[5247,12356,5278],{"emptyLinePlaceholder":5277},[5247,12358,12359,12361,12363,12366],{"class":5249,"line":5454},[5247,12360,6805],{"class":5863},[5247,12362,5867],{"class":5825},[5247,12364,12365],{"class":6204},"\"📊 SGDR Warm Restarts:\"",[5247,12367,5924],{"class":5825},[5247,12369,12370,12372,12374,12376,12379],{"class":5249,"line":5460},[5247,12371,6805],{"class":5863},[5247,12373,5867],{"class":5825},[5247,12375,6601],{"class":5859},[5247,12377,12378],{"class":6204},"\"├─ Перший період (епохи 0-9): cosine decay\"",[5247,12380,5924],{"class":5825},[5247,12382,12383,12385,12387,12389,12392],{"class":5249,"line":5466},[5247,12384,6805],{"class":5863},[5247,12386,5867],{"class":5825},[5247,12388,6601],{"class":5859},[5247,12390,12391],{"class":6204},"\"├─ Restart на епосі 10: LR → 0.1\"",[5247,12393,5924],{"class":5825},[5247,12395,12396,12398,12400,12402,12405],{"class":5249,"line":5472},[5247,12397,6805],{"class":5863},[5247,12399,5867],{"class":5825},[5247,12401,6601],{"class":5859},[5247,12403,12404],{"class":6204},"\"├─ Другий період (епохи 10-29, довжина 20): cosine decay\"",[5247,12406,5924],{"class":5825},[5247,12408,12409,12411,12413,12415,12418],{"class":5249,"line":5477},[5247,12410,6805],{"class":5863},[5247,12412,5867],{"class":5825},[5247,12414,6601],{"class":5859},[5247,12416,12417],{"class":6204},"\"├─ Restart на епосі 30: LR → 0.1\"",[5247,12419,5924],{"class":5825},[5247,12421,12422,12424,12426,12428,12431],{"class":5249,"line":5482},[5247,12423,6805],{"class":5863},[5247,12425,5867],{"class":5825},[5247,12427,6601],{"class":5859},[5247,12429,12430],{"class":6204},"\"└─ Третій період (епохи 30-69, довжина 40): cosine decay\"",[5247,12432,5924],{"class":5825},[7107,12434,12435,12442,12447],{"v-slot:output":5242},[5191,12436,12437],{},[7112,12438],{"alt":12439,"className":12440,"src":12441},"SGDR: періодичні warm restarts для escape з локальних мінімумів",[7116],"\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling\u002F08.png",[5191,12443,7120,12444],{},[5195,12445,12446],{},"SGDR Warm Restarts:",[5625,12448,12449,12452,12455,12458,12461],{},[5628,12450,12451],{},"Перший період (епохи 0-9): cosine decay",[5628,12453,12454],{},"Restart на епосі 10: LR → 0.1",[5628,12456,12457],{},"Другий період (епохи 10-29, довжина 20): cosine decay",[5628,12459,12460],{},"Restart на епосі 30: LR → 0.1",[5628,12462,12463],{},"Третій період (епохи 30-69, довжина 40): cosine decay",[5191,12465,12466],{},[5195,12467,12468],{},"Переваги SGDR:",[5209,12470,12471,12475,12479],{},[5212,12472,12474],{"icon":5644,"title":12473},"🎯 Втеча з локальних мінімумів","Restart LR дозволяє моделі \"виштовхнутися\" з вузьких локальних мінімумів та знайти ширші, краще генералізують розв'язки.",[5212,12476,12478],{"icon":943,"title":12477},"🔄 Ансамбль ефект","Кожен restart можна розглядати як окрему модель. Збережіть checkpoint після кожного циклу та усередніть їхні передбачення (snapshot ensembling).",[5212,12480,12482],{"icon":7282,"title":12481},"📈 Кращі фінальні результати","Емпірично SGDR часто досягає на 0.5-1% кращої accuracy порівняно зі звичайним cosine annealing.",[5191,12484,12485],{},[5195,12486,7984],{},[5625,12488,12489,12492,12495],{},[5628,12490,12491],{},"❌ Складніший у налаштуванні (T_0, T_mult)",[5628,12493,12494],{},"❌ Навчання може бути нестабільним (accuracy \"стрибає\" після restart)",[5628,12496,12497],{},"❌ Потребує довшого тренування (кілька циклів)",[5191,12499,12500,12502],{},[5195,12501,8000],{}," Для змагань (Kaggle), де критична остання крихта точності. Або коли підозрюєте, що модель застряла у поганому локальному мінімумі.",[5712,12504],{},[5544,12506,12508],{"id":12507},"onecyclelr-супер-конвергенція","OneCycleLR — супер-конвергенція",[5191,12510,12511,12514,12515,5623],{},[5195,12512,12513],{},"Ідея (від Leslie Smith, 2018):"," Замість монотонного зменшення LR, використовуйте ",[5195,12516,12517],{},"один великий цикл",[9564,12519,12520,12526],{},[5628,12521,12522,12525],{},[5195,12523,12524],{},"Збільшення"," LR від малого до максимального (50% часу)",[5628,12527,12528,12531],{},[5195,12529,12530],{},"Зменшення"," LR від максимального до мінімального (50% часу)",[5191,12533,12534],{},"Це дозволяє досягти \"super-convergence\" — навчання у 5-10 разів швидше з тією ж accuracy!",[5796,12536,12537,13059],{"execution-count":6658},[5237,12538,12540],{"className":5812,"code":12539,"language":5814,"meta":5242,"style":5242},"# OneCycleLR\noptimizer = optim.SGD(model.parameters(), lr=0.1, momentum=0.9)\n\n# Потрібно знати загальну кількість кроків (не епох!)\ntotal_steps = 100 * 391  # 100 епох × 391 батч\u002Fепоха (CIFAR-10 з batch_size=128)\n\nscheduler = optim.lr_scheduler.OneCycleLR(\n    optimizer,\n    max_lr=0.1,           # Максимальний LR у піку циклу\n    total_steps=total_steps,\n    pct_start=0.3,        # 30% часу — збільшення, 70% — зменшення\n    anneal_strategy='cos', # Косинусоїдальна форма\n    div_factor=25,        # Початковий LR = max_lr \u002F 25 = 0.004\n    final_div_factor=10000 # Фінальний LR = max_lr \u002F 10000 = 0.00001\n)\n\n# Симуляція (кожен \"epoch\" тут — це насправді батч)\nlr_history_onecycle = []\nfor step in range(1000):  # Симулюємо 1000 кроків\n    lr_history_onecycle.append(optimizer.param_groups[0]['lr'])\n    optimizer.step()\n    scheduler.step()\n\n# Візуалізація\nplt.figure(figsize=(14, 6))\nplt.plot(lr_history_onecycle, linewidth=2.5, color='#22c55e', label='OneCycleLR')\nplt.axvline(x=300, color='orange', linestyle='--', alpha=0.5, linewidth=2, label='Пік (30%)')\nplt.xlabel('Training Step (батч)', fontsize=12)\nplt.ylabel('Learning Rate', fontsize=12)\nplt.title('OneCycleLR — один великий цикл (super-convergence)', fontsize=14, fontweight='bold')\nplt.grid(alpha=0.3)\nplt.legend(fontsize=11)\nplt.tight_layout()\nplt.show()\n\nprint(\"📊 OneCycleLR:\")\nprint(f\"├─ Старт (крок 0):      LR = {lr_history_onecycle[0]:.6f}\")\nprint(f\"├─ Пік (крок 300):      LR = {lr_history_onecycle[300]:.6f}\")\nprint(f\"├─ Середина (крок 500): LR = {lr_history_onecycle[500]:.6f}\")\nprint(f\"└─ Фініш (крок 999):    LR = {lr_history_onecycle[999]:.6f}\")\n",[5244,12541,12542,12547,12567,12571,12576,12591,12595,12600,12604,12619,12627,12642,12657,12671,12683,12687,12691,12696,12701,12722,12735,12739,12743,12747,12751,12767,12797,12852,12869,12885,12910,12922,12934,12938,12942,12946,12957,12983,13008,13033],{"__ignoreMap":5242},[5247,12543,12544],{"class":5249,"line":5250},[5247,12545,12546],{"class":5853},"# OneCycleLR\n",[5247,12548,12549,12551,12553,12555,12557,12559,12561,12563,12565],{"class":5249,"line":5256},[5247,12550,7515],{"class":5825},[5247,12552,5951],{"class":5870},[5247,12554,6055],{"class":5825},[5247,12556,6058],{"class":5885},[5247,12558,5948],{"class":5825},[5247,12560,7526],{"class":5870},[5247,12562,6055],{"class":5825},[5247,12564,7531],{"class":5885},[5247,12566,5924],{"class":5825},[5247,12568,12569],{"class":5249,"line":5262},[5247,12570,5278],{"emptyLinePlaceholder":5277},[5247,12572,12573],{"class":5249,"line":5268},[5247,12574,12575],{"class":5853},"# Потрібно знати загальну кількість кроків (не епох!)\n",[5247,12577,12578,12581,12583,12585,12588],{"class":5249,"line":5274},[5247,12579,12580],{"class":5825},"total_steps = ",[5247,12582,9048],{"class":5885},[5247,12584,6886],{"class":5825},[5247,12586,12587],{"class":5885},"391",[5247,12589,12590],{"class":5853},"  # 100 епох × 391 батч\u002Fепоха (CIFAR-10 з batch_size=128)\n",[5247,12592,12593],{"class":5249,"line":5281},[5247,12594,5278],{"emptyLinePlaceholder":5277},[5247,12596,12597],{"class":5249,"line":5287},[5247,12598,12599],{"class":5825},"scheduler = optim.lr_scheduler.OneCycleLR(\n",[5247,12601,12602],{"class":5249,"line":5293},[5247,12603,9653],{"class":5825},[5247,12605,12606,12609,12611,12613,12616],{"class":5249,"line":5299},[5247,12607,12608],{"class":5870},"    max_lr",[5247,12610,6055],{"class":5825},[5247,12612,6058],{"class":5885},[5247,12614,12615],{"class":5825},",           ",[5247,12617,12618],{"class":5853},"# Максимальний LR у піку циклу\n",[5247,12620,12621,12624],{"class":5249,"line":5304},[5247,12622,12623],{"class":5870},"    total_steps",[5247,12625,12626],{"class":5825},"=total_steps,\n",[5247,12628,12629,12632,12634,12636,12639],{"class":5249,"line":5310},[5247,12630,12631],{"class":5870},"    pct_start",[5247,12633,6055],{"class":5825},[5247,12635,6322],{"class":5885},[5247,12637,12638],{"class":5825},",        ",[5247,12640,12641],{"class":5853},"# 30% часу — збільшення, 70% — зменшення\n",[5247,12643,12644,12647,12649,12652,12654],{"class":5249,"line":5316},[5247,12645,12646],{"class":5870},"    anneal_strategy",[5247,12648,6055],{"class":5825},[5247,12650,12651],{"class":6204},"'cos'",[5247,12653,5948],{"class":5825},[5247,12655,12656],{"class":5853},"# Косинусоїдальна форма\n",[5247,12658,12659,12662,12664,12666,12668],{"class":5249,"line":5322},[5247,12660,12661],{"class":5870},"    div_factor",[5247,12663,6055],{"class":5825},[5247,12665,8802],{"class":5885},[5247,12667,12638],{"class":5825},[5247,12669,12670],{"class":5853},"# Початковий LR = max_lr \u002F 25 = 0.004\n",[5247,12672,12673,12676,12678,12680],{"class":5249,"line":5328},[5247,12674,12675],{"class":5870},"    final_div_factor",[5247,12677,6055],{"class":5825},[5247,12679,11837],{"class":5885},[5247,12681,12682],{"class":5853}," # Фінальний LR = max_lr \u002F 10000 = 0.00001\n",[5247,12684,12685],{"class":5249,"line":5334},[5247,12686,5924],{"class":5825},[5247,12688,12689],{"class":5249,"line":5340},[5247,12690,5278],{"emptyLinePlaceholder":5277},[5247,12692,12693],{"class":5249,"line":5346},[5247,12694,12695],{"class":5853},"# Симуляція (кожен \"epoch\" тут — це насправді батч)\n",[5247,12697,12698],{"class":5249,"line":5352},[5247,12699,12700],{"class":5825},"lr_history_onecycle = []\n",[5247,12702,12703,12705,12708,12710,12712,12714,12717,12719],{"class":5249,"line":5358},[5247,12704,6281],{"class":5821},[5247,12706,12707],{"class":5825}," step ",[5247,12709,5984],{"class":5821},[5247,12711,5987],{"class":5863},[5247,12713,5867],{"class":5825},[5247,12715,12716],{"class":5885},"1000",[5247,12718,12006],{"class":5825},[5247,12720,12721],{"class":5853},"# Симулюємо 1000 кроків\n",[5247,12723,12724,12727,12729,12731,12733],{"class":5249,"line":5364},[5247,12725,12726],{"class":5825},"    lr_history_onecycle.append(optimizer.param_groups[",[5247,12728,6216],{"class":5885},[5247,12730,7616],{"class":5825},[5247,12732,7619],{"class":6204},[5247,12734,6267],{"class":5825},[5247,12736,12737],{"class":5249,"line":5369},[5247,12738,7635],{"class":5825},[5247,12740,12741],{"class":5249,"line":5375},[5247,12742,7649],{"class":5825},[5247,12744,12745],{"class":5249,"line":5380},[5247,12746,5278],{"emptyLinePlaceholder":5277},[5247,12748,12749],{"class":5249,"line":5386},[5247,12750,6120],{"class":5853},[5247,12752,12753,12755,12757,12759,12761,12763,12765],{"class":5249,"line":5392},[5247,12754,7662],{"class":5825},[5247,12756,6136],{"class":5870},[5247,12758,6139],{"class":5825},[5247,12760,6565],{"class":5885},[5247,12762,5948],{"class":5825},[5247,12764,6171],{"class":5885},[5247,12766,6150],{"class":5825},[5247,12768,12769,12772,12774,12776,12778,12780,12782,12784,12786,12788,12790,12792,12795],{"class":5249,"line":5398},[5247,12770,12771],{"class":5825},"plt.plot(lr_history_onecycle, ",[5247,12773,6307],{"class":5870},[5247,12775,6055],{"class":5825},[5247,12777,6428],{"class":5885},[5247,12779,5948],{"class":5825},[5247,12781,6418],{"class":5870},[5247,12783,6055],{"class":5825},[5247,12785,6236],{"class":6204},[5247,12787,5948],{"class":5825},[5247,12789,6327],{"class":5870},[5247,12791,6055],{"class":5825},[5247,12793,12794],{"class":6204},"'OneCycleLR'",[5247,12796,5924],{"class":5825},[5247,12798,12799,12802,12804,12806,12809,12811,12813,12815,12817,12819,12821,12823,12825,12827,12829,12831,12833,12835,12837,12839,12841,12843,12845,12847,12850],{"class":5249,"line":5404},[5247,12800,12801],{"class":5825},"plt.axvline(",[5247,12803,8223],{"class":5870},[5247,12805,6055],{"class":5825},[5247,12807,12808],{"class":5885},"300",[5247,12810,5948],{"class":5825},[5247,12812,6418],{"class":5870},[5247,12814,6055],{"class":5825},[5247,12816,11335],{"class":6204},[5247,12818,5948],{"class":5825},[5247,12820,8238],{"class":5870},[5247,12822,6055],{"class":5825},[5247,12824,8243],{"class":6204},[5247,12826,5948],{"class":5825},[5247,12828,6317],{"class":5870},[5247,12830,6055],{"class":5825},[5247,12832,6080],{"class":5885},[5247,12834,5948],{"class":5825},[5247,12836,6307],{"class":5870},[5247,12838,6055],{"class":5825},[5247,12840,6264],{"class":5885},[5247,12842,5948],{"class":5825},[5247,12844,6327],{"class":5870},[5247,12846,6055],{"class":5825},[5247,12848,12849],{"class":6204},"'Пік (30%)'",[5247,12851,5924],{"class":5825},[5247,12853,12854,12856,12859,12861,12863,12865,12867],{"class":5249,"line":5409},[5247,12855,7709],{"class":5825},[5247,12857,12858],{"class":6204},"'Training Step (батч)'",[5247,12860,5948],{"class":5825},[5247,12862,6653],{"class":5870},[5247,12864,6055],{"class":5825},[5247,12866,6500],{"class":5885},[5247,12868,5924],{"class":5825},[5247,12870,12871,12873,12875,12877,12879,12881,12883],{"class":5249,"line":5414},[5247,12872,7727],{"class":5825},[5247,12874,7730],{"class":6204},[5247,12876,5948],{"class":5825},[5247,12878,6653],{"class":5870},[5247,12880,6055],{"class":5825},[5247,12882,6500],{"class":5885},[5247,12884,5924],{"class":5825},[5247,12886,12887,12889,12892,12894,12896,12898,12900,12902,12904,12906,12908],{"class":5249,"line":5419},[5247,12888,7745],{"class":5825},[5247,12890,12891],{"class":6204},"'OneCycleLR — один великий цикл (super-convergence)'",[5247,12893,5948],{"class":5825},[5247,12895,6653],{"class":5870},[5247,12897,6055],{"class":5825},[5247,12899,6565],{"class":5885},[5247,12901,5948],{"class":5825},[5247,12903,6721],{"class":5870},[5247,12905,6055],{"class":5825},[5247,12907,6726],{"class":6204},[5247,12909,5924],{"class":5825},[5247,12911,12912,12914,12916,12918,12920],{"class":5249,"line":5425},[5247,12913,7785],{"class":5825},[5247,12915,6317],{"class":5870},[5247,12917,6055],{"class":5825},[5247,12919,6322],{"class":5885},[5247,12921,5924],{"class":5825},[5247,12923,12924,12926,12928,12930,12932],{"class":5249,"line":5430},[5247,12925,7798],{"class":5825},[5247,12927,6653],{"class":5870},[5247,12929,6055],{"class":5825},[5247,12931,7805],{"class":5885},[5247,12933,5924],{"class":5825},[5247,12935,12936],{"class":5249,"line":5436},[5247,12937,6782],{"class":5825},[5247,12939,12940],{"class":5249,"line":5442},[5247,12941,6788],{"class":5825},[5247,12943,12944],{"class":5249,"line":5448},[5247,12945,5278],{"emptyLinePlaceholder":5277},[5247,12947,12948,12950,12952,12955],{"class":5249,"line":5454},[5247,12949,6805],{"class":5863},[5247,12951,5867],{"class":5825},[5247,12953,12954],{"class":6204},"\"📊 OneCycleLR:\"",[5247,12956,5924],{"class":5825},[5247,12958,12959,12961,12963,12965,12968,12970,12973,12975,12977,12979,12981],{"class":5249,"line":5460},[5247,12960,6805],{"class":5863},[5247,12962,5867],{"class":5825},[5247,12964,6601],{"class":5859},[5247,12966,12967],{"class":6204},"\"├─ Старт (крок 0):      LR = ",[5247,12969,6607],{"class":5859},[5247,12971,12972],{"class":5825},"lr_history_onecycle[",[5247,12974,6216],{"class":5885},[5247,12976,7851],{"class":5825},[5247,12978,8780],{"class":5859},[5247,12980,6817],{"class":6204},[5247,12982,5924],{"class":5825},[5247,12984,12985,12987,12989,12991,12994,12996,12998,13000,13002,13004,13006],{"class":5249,"line":5466},[5247,12986,6805],{"class":5863},[5247,12988,5867],{"class":5825},[5247,12990,6601],{"class":5859},[5247,12992,12993],{"class":6204},"\"├─ Пік (крок 300):      LR = ",[5247,12995,6607],{"class":5859},[5247,12997,12972],{"class":5825},[5247,12999,12808],{"class":5885},[5247,13001,7851],{"class":5825},[5247,13003,8780],{"class":5859},[5247,13005,6817],{"class":6204},[5247,13007,5924],{"class":5825},[5247,13009,13010,13012,13014,13016,13019,13021,13023,13025,13027,13029,13031],{"class":5249,"line":5472},[5247,13011,6805],{"class":5863},[5247,13013,5867],{"class":5825},[5247,13015,6601],{"class":5859},[5247,13017,13018],{"class":6204},"\"├─ Середина (крок 500): LR = ",[5247,13020,6607],{"class":5859},[5247,13022,12972],{"class":5825},[5247,13024,11822],{"class":5885},[5247,13026,7851],{"class":5825},[5247,13028,8780],{"class":5859},[5247,13030,6817],{"class":6204},[5247,13032,5924],{"class":5825},[5247,13034,13035,13037,13039,13041,13044,13046,13048,13051,13053,13055,13057],{"class":5249,"line":5477},[5247,13036,6805],{"class":5863},[5247,13038,5867],{"class":5825},[5247,13040,6601],{"class":5859},[5247,13042,13043],{"class":6204},"\"└─ Фініш (крок 999):    LR = ",[5247,13045,6607],{"class":5859},[5247,13047,12972],{"class":5825},[5247,13049,13050],{"class":5885},"999",[5247,13052,7851],{"class":5825},[5247,13054,8780],{"class":5859},[5247,13056,6817],{"class":6204},[5247,13058,5924],{"class":5825},[7107,13060,13061,13068,13073],{"v-slot:output":5242},[5191,13062,13063],{},[7112,13064],{"alt":13065,"className":13066,"src":13067},"OneCycleLR: швидке збільшення LR, потім тривале зменшення",[7116],"\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling\u002F09.png",[5191,13069,7120,13070],{},[5195,13071,13072],{},"OneCycleLR:",[5625,13074,13075,13078,13081,13084],{},[5628,13076,13077],{},"Старт (крок 0):      LR = 0.004000 (max_lr \u002F 25)",[5628,13079,13080],{},"Пік (крок 300):      LR = 0.100000 (максимум)",[5628,13082,13083],{},"Середина (крок 500): LR = 0.052000 (спад)",[5628,13085,13086],{},"Фініш (крок 999):    LR = 0.000010 (майже нуль)",[5191,13088,13089],{},[5195,13090,13091],{},"Чому це працює:",[9564,13093,13094,13100,13106],{},[5628,13095,13096,13099],{},[5195,13097,13098],{},"Початковий warm-up:"," Великий LR на початку допомагає швидко знайти \"хороший регіон\" ландшафту втрат",[5628,13101,13102,13105],{},[5195,13103,13104],{},"Регуляризаційний ефект:"," Великий LR діє як регуляризатор, запобігаючи перенавчанню",[5628,13107,13108,13111],{},[5195,13109,13110],{},"Fine-tuning наприкінці:"," Малий LR дозволяє точно налаштуватися у мінімумі",[5191,13113,13114],{},[5195,13115,7968],{},[5625,13117,13118,13124,13127],{},[5628,13119,9525,13120,13123],{},[5195,13121,13122],{},"Найшвидша конвергенція"," серед усіх schedulers",[5628,13125,13126],{},"✅ Часто досягає кращої accuracy за менше епох",[5628,13128,13129],{},"✅ Менше гіперпараметрів для налаштування",[5191,13131,13132],{},[5195,13133,7984],{},[5625,13135,13136,13143],{},[5628,13137,13138,13139,13142],{},"❌ Потрібно точно знати ",[5244,13140,13141],{},"total_steps"," заздалегідь",[5628,13144,13145,13146,13149],{},"❌ Чутливий до ",[5244,13147,13148],{},"max_lr"," (потрібен LR range test)",[5191,13151,13152,13154],{},[5195,13153,8000],{}," Коли час навчання критичний (продакшн deadline, GPU costs). Особливо популярний у fast.ai community.",[5712,13156],{},[5186,13158,13160],{"id":13159},"експеримент-порівняння-schedulers-на-cifar-10","Експеримент: порівняння schedulers на CIFAR-10",[5191,13162,13163],{},"Проведемо контрольований експеримент, щоб емпірично порівняти п'ять стратегій scheduling на ResNet-18:",[9564,13165,13166,13172,13177,13182,13187],{},[5628,13167,13168,13171],{},[5195,13169,13170],{},"Фіксований LR"," (baseline)",[5628,13173,13174],{},[5195,13175,13176],{},"StepLR",[5628,13178,13179],{},[5195,13180,13181],{},"CosineAnnealingLR",[5628,13183,13184],{},[5195,13185,13186],{},"ReduceLROnPlateau",[5628,13188,13189],{},[5195,13190,13191],{},"Warm-up + CosineAnnealing",[5544,13193,13195],{"id":13194},"експериментальна-конфігурація","Експериментальна конфігурація",[5209,13197,13198,13215,13232],{},[5212,13199,13201,13204],{"icon":255,"title":13200},"🏗️ Модель",[5191,13202,13203],{},"ResNet-18 (адаптований для CIFAR-10)",[5625,13205,13206,13209,13212],{},[5628,13207,13208],{},"11.2M параметрів",[5628,13210,13211],{},"Batch Normalization після кожного Conv",[5628,13213,13214],{},"Без Dropout (ResNet не потребує)",[5212,13216,13218,13221],{"icon":2865,"title":13217},"📊 Датасет",[5191,13219,13220],{},"CIFAR-10",[5625,13222,13223,13226,13229],{},[5628,13224,13225],{},"Train: 50,000 зображень",[5628,13227,13228],{},"Test: 10,000 зображень",[5628,13230,13231],{},"Data Augmentation: RandomCrop, HorizontalFlip",[5212,13233,13236],{"icon":13234,"title":13235},"i-lucide-settings","⚙️ Тренування",[5625,13237,13238,13241,13244,13247],{},[5628,13239,13240],{},"Optimizer: SGD (momentum=0.9, weight_decay=5e-4)",[5628,13242,13243],{},"Batch size: 128",[5628,13245,13246],{},"Епохи: 100",[5628,13248,13249],{},"Початковий LR: 0.1 (для всіх, крім warm-up)",[5544,13251,13253],{"id":13252},"код-експерименту","Код експерименту",[5796,13255,13256,15330],{"execution-count":6555},[5237,13257,13259],{"className":5812,"code":13258,"language":5814,"meta":5242,"style":5242},"import torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader\nfrom torchvision import datasets, transforms\nimport time\n\n# Підготовка даних\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\nprint(f\"🖥️ Пристрій: {device}\\n\")\n\ntransform_train = transforms.Compose([\n    transforms.RandomCrop(32, padding=4),\n    transforms.RandomHorizontalFlip(),\n    transforms.ToTensor(),\n    transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2470, 0.2435, 0.2616))\n])\n\ntransform_test = transforms.Compose([\n    transforms.ToTensor(),\n    transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2470, 0.2435, 0.2616))\n])\n\ntrain_dataset = datasets.CIFAR10(root='.\u002Fdata', train=True, download=True, transform=transform_train)\ntest_dataset = datasets.CIFAR10(root='.\u002Fdata', train=False, download=True, transform=transform_test)\n\ntrain_loader = DataLoader(train_dataset, batch_size=128, shuffle=True, num_workers=2)\ntest_loader = DataLoader(test_dataset, batch_size=128, shuffle=False, num_workers=2)\n\n# Імпортуємо ResNet-18 (припускаємо, що ми реалізували його у попередній статті)\nfrom torchvision import models\nresnet18 = models.resnet18(num_classes=10)\n# Адаптація для CIFAR-10: зменшимо початковий conv\nresnet18.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1, bias=False)\nresnet18.maxpool = nn.Identity()  # Вимкнемо maxpool для малих зображень\n\ndef train_with_scheduler(model, scheduler_name, scheduler, num_epochs=100):\n    \"\"\"Тренування моделі з заданим scheduler\"\"\"\n    model = model.to(device)\n    criterion = nn.CrossEntropyLoss()\n    optimizer = optim.SGD(model.parameters(), lr=0.1, momentum=0.9, weight_decay=5e-4)\n    \n    history = {'train_loss': [], 'train_acc': [], 'test_loss': [], 'test_acc': [], 'lr': []}\n    \n    print(f\"\\n🚀 Початок навчання: {scheduler_name}\")\n    print(\"=\" * 80)\n    start_time = time.time()\n    \n    best_acc = 0\n    \n    for epoch in range(1, num_epochs + 1):\n        # Тренування\n        model.train()\n        running_loss = 0.0\n        correct = 0\n        total = 0\n        \n        for images, labels in train_loader:\n            images, labels = images.to(device), labels.to(device)\n            \n            optimizer.zero_grad()\n            outputs = model(images)\n            loss = criterion(outputs, labels)\n            loss.backward()\n            optimizer.step()\n            \n            running_loss += loss.item() * images.size(0)\n            _, predicted = outputs.max(1)\n            total += labels.size(0)\n            correct += predicted.eq(labels).sum().item()\n        \n        train_loss = running_loss \u002F total\n        train_acc = 100. * correct \u002F total\n        \n        # Валідація\n        model.eval()\n        running_loss = 0.0\n        correct = 0\n        total = 0\n        \n        with torch.no_grad():\n            for images, labels in test_loader:\n                images, labels = images.to(device), labels.to(device)\n                outputs = model(images)\n                loss = criterion(outputs, labels)\n                \n                running_loss += loss.item() * images.size(0)\n                _, predicted = outputs.max(1)\n                total += labels.size(0)\n                correct += predicted.eq(labels).sum().item()\n        \n        test_loss = running_loss \u002F total\n        test_acc = 100. * correct \u002F total\n        \n        # Збереження історії\n        history['train_loss'].append(train_loss)\n        history['train_acc'].append(train_acc)\n        history['test_loss'].append(test_loss)\n        history['test_acc'].append(test_acc)\n        history['lr'].append(optimizer.param_groups[0]['lr'])\n        \n        # Оновлення scheduler\n        if scheduler_name == \"ReduceLROnPlateau\":\n            scheduler.step(test_loss)\n        elif scheduler is not None:\n            scheduler.step()\n        \n        if test_acc > best_acc:\n            best_acc = test_acc\n        \n        # Виведення прогресу\n        if epoch % 20 == 0 or epoch == 1:\n            print(f\"Epoch {epoch:3d} | Train: {train_loss:.4f} \u002F {train_acc:.2f}% | \"\n                  f\"Test: {test_loss:.4f} \u002F {test_acc:.2f}% | LR: {history['lr'][-1]:.6f}\")\n    \n    elapsed = time.time() - start_time\n    print(\"=\" * 80)\n    print(f\"✅ Завершено за {elapsed\u002F60:.1f} хв | Найкраща accuracy: {best_acc:.2f}%\\n\")\n    \n    return history\n\n# Експеримент 1: Фіксований LR (baseline)\nmodel_fixed = models.resnet18(num_classes=10)\nmodel_fixed.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1, bias=False)\nmodel_fixed.maxpool = nn.Identity()\n\nhistory_fixed = train_with_scheduler(model_fixed, \"Fixed LR\", scheduler=None, num_epochs=100)\n\n# Експеримент 2: StepLR\nmodel_step = models.resnet18(num_classes=10)\nmodel_step.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1, bias=False)\nmodel_step.maxpool = nn.Identity()\n\noptimizer_step = optim.SGD(model_step.parameters(), lr=0.1, momentum=0.9, weight_decay=5e-4)\nscheduler_step = optim.lr_scheduler.StepLR(optimizer_step, step_size=30, gamma=0.1)\n\nhistory_step = train_with_scheduler(model_step, \"StepLR\", scheduler_step, num_epochs=100)\n\n# Експеримент 3: CosineAnnealingLR\nmodel_cosine = models.resnet18(num_classes=10)\nmodel_cosine.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1, bias=False)\nmodel_cosine.maxpool = nn.Identity()\n\noptimizer_cosine = optim.SGD(model_cosine.parameters(), lr=0.1, momentum=0.9, weight_decay=5e-4)\nscheduler_cosine = optim.lr_scheduler.CosineAnnealingLR(optimizer_cosine, T_max=100, eta_min=1e-6)\n\nhistory_cosine = train_with_scheduler(model_cosine, \"CosineAnnealingLR\", scheduler_cosine, num_epochs=100)\n\n# Експеримент 4: ReduceLROnPlateau\nmodel_plateau = models.resnet18(num_classes=10)\nmodel_plateau.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1, bias=False)\nmodel_plateau.maxpool = nn.Identity()\n\noptimizer_plateau = optim.SGD(model_plateau.parameters(), lr=0.1, momentum=0.9, weight_decay=5e-4)\nscheduler_plateau = optim.lr_scheduler.ReduceLROnPlateau(\n    optimizer_plateau, mode='min', factor=0.1, patience=10, verbose=True\n)\n\nhistory_plateau = train_with_scheduler(model_plateau, \"ReduceLROnPlateau\", scheduler_plateau, num_epochs=100)\n\n# Експеримент 5: Warm-up + CosineAnnealing\nmodel_warmup = models.resnet18(num_classes=10)\nmodel_warmup.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1, bias=False)\nmodel_warmup.maxpool = nn.Identity()\n\noptimizer_warmup = optim.SGD(model_warmup.parameters(), lr=0.1, momentum=0.9, weight_decay=5e-4)\nscheduler_warmup = WarmupCosineScheduler(optimizer_warmup, warmup_epochs=5, total_epochs=100)\n\nhistory_warmup = train_with_scheduler(model_warmup, \"Warm-up + Cosine\", scheduler_warmup, num_epochs=100)\n",[5244,13260,13261,13267,13279,13289,13301,13313,13320,13324,13329,13349,13373,13377,13382,13402,13407,13412,13448,13452,13456,13461,13465,13493,13497,13501,13540,13574,13578,13611,13640,13644,13649,13660,13674,13679,13728,13736,13740,13773,13778,13783,13788,13819,13823,13854,13858,13883,13899,13904,13908,13915,13919,13940,13945,13950,13957,13964,13971,13975,13987,13992,13997,14002,14007,14012,14017,14022,14026,14035,14044,14053,14058,14062,14067,14077,14081,14086,14091,14097,14103,14109,14113,14121,14133,14138,14143,14148,14153,14162,14171,14180,14185,14189,14194,14203,14207,14213,14224,14234,14244,14254,14272,14277,14283,14296,14302,14322,14328,14333,14341,14347,14352,14358,14383,14428,14476,14481,14487,14502,14543,14548,14556,14561,14567,14581,14627,14633,14638,14666,14671,14677,14691,14737,14743,14748,14778,14800,14805,14825,14830,14836,14850,14896,14902,14907,14937,14959,14964,14984,14989,14995,15009,15055,15061,15066,15096,15102,15142,15147,15152,15171,15176,15182,15196,15242,15248,15253,15283,15305,15310],{"__ignoreMap":5242},[5247,13262,13263,13265],{"class":5249,"line":5250},[5247,13264,5822],{"class":5821},[5247,13266,7466],{"class":5825},[5247,13268,13269,13271,13274,13276],{"class":5249,"line":5256},[5247,13270,5822],{"class":5821},[5247,13272,13273],{"class":5825}," torch.nn ",[5247,13275,5829],{"class":5821},[5247,13277,13278],{"class":5825}," nn\n",[5247,13280,13281,13283,13285,13287],{"class":5249,"line":5262},[5247,13282,5822],{"class":5821},[5247,13284,7473],{"class":5825},[5247,13286,5829],{"class":5821},[5247,13288,7478],{"class":5825},[5247,13290,13291,13293,13296,13298],{"class":5249,"line":5268},[5247,13292,11791],{"class":5821},[5247,13294,13295],{"class":5825}," torch.utils.data ",[5247,13297,5822],{"class":5821},[5247,13299,13300],{"class":5825}," DataLoader\n",[5247,13302,13303,13305,13308,13310],{"class":5249,"line":5274},[5247,13304,11791],{"class":5821},[5247,13306,13307],{"class":5825}," torchvision ",[5247,13309,5822],{"class":5821},[5247,13311,13312],{"class":5825}," datasets, transforms\n",[5247,13314,13315,13317],{"class":5249,"line":5281},[5247,13316,5822],{"class":5821},[5247,13318,13319],{"class":5825}," time\n",[5247,13321,13322],{"class":5249,"line":5287},[5247,13323,5278],{"emptyLinePlaceholder":5277},[5247,13325,13326],{"class":5249,"line":5293},[5247,13327,13328],{"class":5853},"# Підготовка даних\n",[5247,13330,13331,13334,13337,13339,13342,13344,13347],{"class":5249,"line":5299},[5247,13332,13333],{"class":5825},"device = torch.device(",[5247,13335,13336],{"class":6204},"'cuda'",[5247,13338,7010],{"class":5821},[5247,13340,13341],{"class":5825}," torch.cuda.is_available() ",[5247,13343,7016],{"class":5821},[5247,13345,13346],{"class":6204}," 'cpu'",[5247,13348,5924],{"class":5825},[5247,13350,13351,13353,13355,13357,13360,13362,13365,13367,13369,13371],{"class":5249,"line":5304},[5247,13352,6805],{"class":5863},[5247,13354,5867],{"class":5825},[5247,13356,6601],{"class":5859},[5247,13358,13359],{"class":6204},"\"🖥️ Пристрій: ",[5247,13361,6607],{"class":5859},[5247,13363,13364],{"class":5825},"device",[5247,13366,6613],{"class":5859},[5247,13368,6814],{"class":6813},[5247,13370,6817],{"class":6204},[5247,13372,5924],{"class":5825},[5247,13374,13375],{"class":5249,"line":5310},[5247,13376,5278],{"emptyLinePlaceholder":5277},[5247,13378,13379],{"class":5249,"line":5316},[5247,13380,13381],{"class":5825},"transform_train = transforms.Compose([\n",[5247,13383,13384,13387,13390,13392,13395,13397,13399],{"class":5249,"line":5322},[5247,13385,13386],{"class":5825},"    transforms.RandomCrop(",[5247,13388,13389],{"class":5885},"32",[5247,13391,5948],{"class":5825},[5247,13393,13394],{"class":5870},"padding",[5247,13396,6055],{"class":5825},[5247,13398,6518],{"class":5885},[5247,13400,13401],{"class":5825},"),\n",[5247,13403,13404],{"class":5249,"line":5328},[5247,13405,13406],{"class":5825},"    transforms.RandomHorizontalFlip(),\n",[5247,13408,13409],{"class":5249,"line":5334},[5247,13410,13411],{"class":5825},"    transforms.ToTensor(),\n",[5247,13413,13414,13417,13420,13422,13425,13427,13430,13433,13436,13438,13441,13443,13446],{"class":5249,"line":5340},[5247,13415,13416],{"class":5825},"    transforms.Normalize((",[5247,13418,13419],{"class":5885},"0.4914",[5247,13421,5948],{"class":5825},[5247,13423,13424],{"class":5885},"0.4822",[5247,13426,5948],{"class":5825},[5247,13428,13429],{"class":5885},"0.4465",[5247,13431,13432],{"class":5825},"), (",[5247,13434,13435],{"class":5885},"0.2470",[5247,13437,5948],{"class":5825},[5247,13439,13440],{"class":5885},"0.2435",[5247,13442,5948],{"class":5825},[5247,13444,13445],{"class":5885},"0.2616",[5247,13447,6150],{"class":5825},[5247,13449,13450],{"class":5249,"line":5346},[5247,13451,6267],{"class":5825},[5247,13453,13454],{"class":5249,"line":5352},[5247,13455,5278],{"emptyLinePlaceholder":5277},[5247,13457,13458],{"class":5249,"line":5358},[5247,13459,13460],{"class":5825},"transform_test = transforms.Compose([\n",[5247,13462,13463],{"class":5249,"line":5364},[5247,13464,13411],{"class":5825},[5247,13466,13467,13469,13471,13473,13475,13477,13479,13481,13483,13485,13487,13489,13491],{"class":5249,"line":5369},[5247,13468,13416],{"class":5825},[5247,13470,13419],{"class":5885},[5247,13472,5948],{"class":5825},[5247,13474,13424],{"class":5885},[5247,13476,5948],{"class":5825},[5247,13478,13429],{"class":5885},[5247,13480,13432],{"class":5825},[5247,13482,13435],{"class":5885},[5247,13484,5948],{"class":5825},[5247,13486,13440],{"class":5885},[5247,13488,5948],{"class":5825},[5247,13490,13445],{"class":5885},[5247,13492,6150],{"class":5825},[5247,13494,13495],{"class":5249,"line":5375},[5247,13496,6267],{"class":5825},[5247,13498,13499],{"class":5249,"line":5380},[5247,13500,5278],{"emptyLinePlaceholder":5277},[5247,13502,13503,13506,13509,13511,13514,13516,13519,13521,13523,13525,13528,13530,13532,13534,13537],{"class":5249,"line":5386},[5247,13504,13505],{"class":5825},"train_dataset = datasets.CIFAR10(",[5247,13507,13508],{"class":5870},"root",[5247,13510,6055],{"class":5825},[5247,13512,13513],{"class":6204},"'.\u002Fdata'",[5247,13515,5948],{"class":5825},[5247,13517,13518],{"class":5870},"train",[5247,13520,6055],{"class":5825},[5247,13522,9984],{"class":5859},[5247,13524,5948],{"class":5825},[5247,13526,13527],{"class":5870},"download",[5247,13529,6055],{"class":5825},[5247,13531,9984],{"class":5859},[5247,13533,5948],{"class":5825},[5247,13535,13536],{"class":5870},"transform",[5247,13538,13539],{"class":5825},"=transform_train)\n",[5247,13541,13542,13545,13547,13549,13551,13553,13555,13557,13559,13561,13563,13565,13567,13569,13571],{"class":5249,"line":5392},[5247,13543,13544],{"class":5825},"test_dataset = datasets.CIFAR10(",[5247,13546,13508],{"class":5870},[5247,13548,6055],{"class":5825},[5247,13550,13513],{"class":6204},[5247,13552,5948],{"class":5825},[5247,13554,13518],{"class":5870},[5247,13556,6055],{"class":5825},[5247,13558,9708],{"class":5859},[5247,13560,5948],{"class":5825},[5247,13562,13527],{"class":5870},[5247,13564,6055],{"class":5825},[5247,13566,9984],{"class":5859},[5247,13568,5948],{"class":5825},[5247,13570,13536],{"class":5870},[5247,13572,13573],{"class":5825},"=transform_test)\n",[5247,13575,13576],{"class":5249,"line":5398},[5247,13577,5278],{"emptyLinePlaceholder":5277},[5247,13579,13580,13583,13586,13588,13591,13593,13596,13598,13600,13602,13605,13607,13609],{"class":5249,"line":5404},[5247,13581,13582],{"class":5825},"train_loader = DataLoader(train_dataset, ",[5247,13584,13585],{"class":5870},"batch_size",[5247,13587,6055],{"class":5825},[5247,13589,13590],{"class":5885},"128",[5247,13592,5948],{"class":5825},[5247,13594,13595],{"class":5870},"shuffle",[5247,13597,6055],{"class":5825},[5247,13599,9984],{"class":5859},[5247,13601,5948],{"class":5825},[5247,13603,13604],{"class":5870},"num_workers",[5247,13606,6055],{"class":5825},[5247,13608,6264],{"class":5885},[5247,13610,5924],{"class":5825},[5247,13612,13613,13616,13618,13620,13622,13624,13626,13628,13630,13632,13634,13636,13638],{"class":5249,"line":5409},[5247,13614,13615],{"class":5825},"test_loader = DataLoader(test_dataset, ",[5247,13617,13585],{"class":5870},[5247,13619,6055],{"class":5825},[5247,13621,13590],{"class":5885},[5247,13623,5948],{"class":5825},[5247,13625,13595],{"class":5870},[5247,13627,6055],{"class":5825},[5247,13629,9708],{"class":5859},[5247,13631,5948],{"class":5825},[5247,13633,13604],{"class":5870},[5247,13635,6055],{"class":5825},[5247,13637,6264],{"class":5885},[5247,13639,5924],{"class":5825},[5247,13641,13642],{"class":5249,"line":5414},[5247,13643,5278],{"emptyLinePlaceholder":5277},[5247,13645,13646],{"class":5249,"line":5419},[5247,13647,13648],{"class":5853},"# Імпортуємо ResNet-18 (припускаємо, що ми реалізували його у попередній статті)\n",[5247,13650,13651,13653,13655,13657],{"class":5249,"line":5425},[5247,13652,11791],{"class":5821},[5247,13654,13307],{"class":5825},[5247,13656,5822],{"class":5821},[5247,13658,13659],{"class":5825}," models\n",[5247,13661,13662,13665,13668,13670,13672],{"class":5249,"line":5430},[5247,13663,13664],{"class":5825},"resnet18 = models.resnet18(",[5247,13666,13667],{"class":5870},"num_classes",[5247,13669,6055],{"class":5825},[5247,13671,6555],{"class":5885},[5247,13673,5924],{"class":5825},[5247,13675,13676],{"class":5249,"line":5436},[5247,13677,13678],{"class":5853},"# Адаптація для CIFAR-10: зменшимо початковий conv\n",[5247,13680,13681,13684,13686,13688,13691,13693,13696,13698,13700,13702,13705,13707,13709,13711,13713,13715,13717,13719,13722,13724,13726],{"class":5249,"line":5442},[5247,13682,13683],{"class":5825},"resnet18.conv1 = nn.Conv2d(",[5247,13685,5886],{"class":5885},[5247,13687,5948],{"class":5825},[5247,13689,13690],{"class":5885},"64",[5247,13692,5948],{"class":5825},[5247,13694,13695],{"class":5870},"kernel_size",[5247,13697,6055],{"class":5825},[5247,13699,5886],{"class":5885},[5247,13701,5948],{"class":5825},[5247,13703,13704],{"class":5870},"stride",[5247,13706,6055],{"class":5825},[5247,13708,5808],{"class":5885},[5247,13710,5948],{"class":5825},[5247,13712,13394],{"class":5870},[5247,13714,6055],{"class":5825},[5247,13716,5808],{"class":5885},[5247,13718,5948],{"class":5825},[5247,13720,13721],{"class":5870},"bias",[5247,13723,6055],{"class":5825},[5247,13725,9708],{"class":5859},[5247,13727,5924],{"class":5825},[5247,13729,13730,13733],{"class":5249,"line":5448},[5247,13731,13732],{"class":5825},"resnet18.maxpool = nn.Identity()  ",[5247,13734,13735],{"class":5853},"# Вимкнемо maxpool для малих зображень\n",[5247,13737,13738],{"class":5249,"line":5454},[5247,13739,5278],{"emptyLinePlaceholder":5277},[5247,13741,13742,13744,13747,13749,13752,13754,13757,13759,13762,13764,13767,13769,13771],{"class":5249,"line":5460},[5247,13743,5860],{"class":5859},[5247,13745,13746],{"class":5863}," train_with_scheduler",[5247,13748,5867],{"class":5825},[5247,13750,13751],{"class":5870},"model",[5247,13753,5948],{"class":5825},[5247,13755,13756],{"class":5870},"scheduler_name",[5247,13758,5948],{"class":5825},[5247,13760,13761],{"class":5870},"scheduler",[5247,13763,5948],{"class":5825},[5247,13765,13766],{"class":5870},"num_epochs",[5247,13768,6055],{"class":5825},[5247,13770,9048],{"class":5885},[5247,13772,5874],{"class":5825},[5247,13774,13775],{"class":5249,"line":5466},[5247,13776,13777],{"class":6204},"    \"\"\"Тренування моделі з заданим scheduler\"\"\"\n",[5247,13779,13780],{"class":5249,"line":5472},[5247,13781,13782],{"class":5825},"    model = model.to(device)\n",[5247,13784,13785],{"class":5249,"line":5477},[5247,13786,13787],{"class":5825},"    criterion = nn.CrossEntropyLoss()\n",[5247,13789,13790,13793,13795,13797,13799,13801,13803,13805,13807,13809,13812,13814,13817],{"class":5249,"line":5482},[5247,13791,13792],{"class":5825},"    optimizer = optim.SGD(model.parameters(), ",[5247,13794,5951],{"class":5870},[5247,13796,6055],{"class":5825},[5247,13798,6058],{"class":5885},[5247,13800,5948],{"class":5825},[5247,13802,7526],{"class":5870},[5247,13804,6055],{"class":5825},[5247,13806,7531],{"class":5885},[5247,13808,5948],{"class":5825},[5247,13810,13811],{"class":5870},"weight_decay",[5247,13813,6055],{"class":5825},[5247,13815,13816],{"class":5885},"5e-4",[5247,13818,5924],{"class":5825},[5247,13820,13821],{"class":5249,"line":5488},[5247,13822,5973],{"class":5825},[5247,13824,13825,13828,13831,13834,13837,13839,13842,13844,13847,13849,13851],{"class":5249,"line":5493},[5247,13826,13827],{"class":5825},"    history = {",[5247,13829,13830],{"class":6204},"'train_loss'",[5247,13832,13833],{"class":5825},": [], ",[5247,13835,13836],{"class":6204},"'train_acc'",[5247,13838,13833],{"class":5825},[5247,13840,13841],{"class":6204},"'test_loss'",[5247,13843,13833],{"class":5825},[5247,13845,13846],{"class":6204},"'test_acc'",[5247,13848,13833],{"class":5825},[5247,13850,7619],{"class":6204},[5247,13852,13853],{"class":5825},": []}\n",[5247,13855,13856],{"class":5249,"line":5499},[5247,13857,5973],{"class":5825},[5247,13859,13860,13862,13864,13866,13868,13870,13873,13875,13877,13879,13881],{"class":5249,"line":5505},[5247,13861,7058],{"class":5863},[5247,13863,5867],{"class":5825},[5247,13865,6601],{"class":5859},[5247,13867,6817],{"class":6204},[5247,13869,6814],{"class":6813},[5247,13871,13872],{"class":6204},"🚀 Початок навчання: ",[5247,13874,6607],{"class":5859},[5247,13876,13756],{"class":5825},[5247,13878,6613],{"class":5859},[5247,13880,6817],{"class":6204},[5247,13882,5924],{"class":5825},[5247,13884,13885,13887,13889,13892,13894,13897],{"class":5249,"line":5510},[5247,13886,7058],{"class":5863},[5247,13888,5867],{"class":5825},[5247,13890,13891],{"class":6204},"\"=\"",[5247,13893,6886],{"class":5825},[5247,13895,13896],{"class":5885},"80",[5247,13898,5924],{"class":5825},[5247,13900,13901],{"class":5249,"line":5516},[5247,13902,13903],{"class":5825},"    start_time = time.time()\n",[5247,13905,13906],{"class":5249,"line":5522},[5247,13907,5973],{"class":5825},[5247,13909,13910,13913],{"class":5249,"line":5528},[5247,13911,13912],{"class":5825},"    best_acc = ",[5247,13914,10884],{"class":5885},[5247,13916,13917],{"class":5249,"line":5534},[5247,13918,5973],{"class":5825},[5247,13920,13921,13923,13925,13927,13929,13931,13933,13936,13938],{"class":5249,"line":5539},[5247,13922,5978],{"class":5821},[5247,13924,7599],{"class":5825},[5247,13926,5984],{"class":5821},[5247,13928,5987],{"class":5863},[5247,13930,5867],{"class":5825},[5247,13932,5808],{"class":5885},[5247,13934,13935],{"class":5825},", num_epochs + ",[5247,13937,5808],{"class":5885},[5247,13939,5874],{"class":5825},[5247,13941,13942],{"class":5249,"line":6401},[5247,13943,13944],{"class":5853},"        # Тренування\n",[5247,13946,13947],{"class":5249,"line":6407},[5247,13948,13949],{"class":5825},"        model.train()\n",[5247,13951,13952,13955],{"class":5249,"line":6434},[5247,13953,13954],{"class":5825},"        running_loss = ",[5247,13956,6033],{"class":5885},[5247,13958,13959,13962],{"class":5249,"line":6464},[5247,13960,13961],{"class":5825},"        correct = ",[5247,13963,10884],{"class":5885},[5247,13965,13966,13969],{"class":5249,"line":6469},[5247,13967,13968],{"class":5825},"        total = ",[5247,13970,10884],{"class":5885},[5247,13972,13973],{"class":5249,"line":6475},[5247,13974,11033],{"class":5825},[5247,13976,13977,13979,13982,13984],{"class":5249,"line":6523},[5247,13978,11038],{"class":5821},[5247,13980,13981],{"class":5825}," images, labels ",[5247,13983,5984],{"class":5821},[5247,13985,13986],{"class":5825}," train_loader:\n",[5247,13988,13989],{"class":5249,"line":6528},[5247,13990,13991],{"class":5825},"            images, labels = images.to(device), labels.to(device)\n",[5247,13993,13994],{"class":5249,"line":6534},[5247,13995,13996],{"class":5825},"            \n",[5247,13998,13999],{"class":5249,"line":6581},[5247,14000,14001],{"class":5825},"            optimizer.zero_grad()\n",[5247,14003,14004],{"class":5249,"line":6595},[5247,14005,14006],{"class":5825},"            outputs = model(images)\n",[5247,14008,14009],{"class":5249,"line":6626},[5247,14010,14011],{"class":5825},"            loss = criterion(outputs, labels)\n",[5247,14013,14014],{"class":5249,"line":6663},[5247,14015,14016],{"class":5825},"            loss.backward()\n",[5247,14018,14019],{"class":5249,"line":6668},[5247,14020,14021],{"class":5825},"            optimizer.step()\n",[5247,14023,14024],{"class":5249,"line":6687},[5247,14025,13996],{"class":5825},[5247,14027,14028,14031,14033],{"class":5249,"line":6706},[5247,14029,14030],{"class":5825},"            running_loss += loss.item() * images.size(",[5247,14032,6216],{"class":5885},[5247,14034,5924],{"class":5825},[5247,14036,14037,14040,14042],{"class":5249,"line":6731},[5247,14038,14039],{"class":5825},"            _, predicted = outputs.max(",[5247,14041,5808],{"class":5885},[5247,14043,5924],{"class":5825},[5247,14045,14046,14049,14051],{"class":5249,"line":6745},[5247,14047,14048],{"class":5825},"            total += labels.size(",[5247,14050,6216],{"class":5885},[5247,14052,5924],{"class":5825},[5247,14054,14055],{"class":5249,"line":6759},[5247,14056,14057],{"class":5825},"            correct += predicted.eq(labels).sum().item()\n",[5247,14059,14060],{"class":5249,"line":6774},[5247,14061,11033],{"class":5825},[5247,14063,14064],{"class":5249,"line":6779},[5247,14065,14066],{"class":5825},"        train_loss = running_loss \u002F total\n",[5247,14068,14069,14072,14074],{"class":5249,"line":6785},[5247,14070,14071],{"class":5825},"        train_acc = ",[5247,14073,9048],{"class":5885},[5247,14075,14076],{"class":5825},". * correct \u002F total\n",[5247,14078,14079],{"class":5249,"line":6791},[5247,14080,11033],{"class":5825},[5247,14082,14083],{"class":5249,"line":6796},[5247,14084,14085],{"class":5853},"        # Валідація\n",[5247,14087,14088],{"class":5249,"line":6802},[5247,14089,14090],{"class":5825},"        model.eval()\n",[5247,14092,14093,14095],{"class":5249,"line":6822},[5247,14094,13954],{"class":5825},[5247,14096,6033],{"class":5885},[5247,14098,14099,14101],{"class":5249,"line":6876},[5247,14100,13961],{"class":5825},[5247,14102,10884],{"class":5885},[5247,14104,14105,14107],{"class":5249,"line":6894},[5247,14106,13968],{"class":5825},[5247,14108,10884],{"class":5885},[5247,14110,14111],{"class":5249,"line":6899},[5247,14112,11033],{"class":5825},[5247,14114,14115,14118],{"class":5249,"line":6911},[5247,14116,14117],{"class":5821},"        with",[5247,14119,14120],{"class":5825}," torch.no_grad():\n",[5247,14122,14123,14126,14128,14130],{"class":5249,"line":6921},[5247,14124,14125],{"class":5821},"            for",[5247,14127,13981],{"class":5825},[5247,14129,5984],{"class":5821},[5247,14131,14132],{"class":5825}," test_loader:\n",[5247,14134,14135],{"class":5249,"line":6927},[5247,14136,14137],{"class":5825},"                images, labels = images.to(device), labels.to(device)\n",[5247,14139,14140],{"class":5249,"line":6932},[5247,14141,14142],{"class":5825},"                outputs = model(images)\n",[5247,14144,14145],{"class":5249,"line":6938},[5247,14146,14147],{"class":5825},"                loss = criterion(outputs, labels)\n",[5247,14149,14150],{"class":5249,"line":6947},[5247,14151,14152],{"class":5825},"                \n",[5247,14154,14155,14158,14160],{"class":5249,"line":6963},[5247,14156,14157],{"class":5825},"                running_loss += loss.item() * images.size(",[5247,14159,6216],{"class":5885},[5247,14161,5924],{"class":5825},[5247,14163,14164,14167,14169],{"class":5249,"line":6984},[5247,14165,14166],{"class":5825},"                _, predicted = outputs.max(",[5247,14168,5808],{"class":5885},[5247,14170,5924],{"class":5825},[5247,14172,14173,14176,14178],{"class":5249,"line":6990},[5247,14174,14175],{"class":5825},"                total += labels.size(",[5247,14177,6216],{"class":5885},[5247,14179,5924],{"class":5825},[5247,14181,14182],{"class":5249,"line":6996},[5247,14183,14184],{"class":5825},"                correct += predicted.eq(labels).sum().item()\n",[5247,14186,14187],{"class":5249,"line":7001},[5247,14188,11033],{"class":5825},[5247,14190,14191],{"class":5249,"line":7022},[5247,14192,14193],{"class":5825},"        test_loss = running_loss \u002F total\n",[5247,14195,14196,14199,14201],{"class":5249,"line":7050},[5247,14197,14198],{"class":5825},"        test_acc = ",[5247,14200,9048],{"class":5885},[5247,14202,14076],{"class":5825},[5247,14204,14205],{"class":5249,"line":7055},[5247,14206,11033],{"class":5825},[5247,14208,14210],{"class":5249,"line":14209},95,[5247,14211,14212],{"class":5853},"        # Збереження історії\n",[5247,14214,14216,14219,14221],{"class":5249,"line":14215},96,[5247,14217,14218],{"class":5825},"        history[",[5247,14220,13830],{"class":6204},[5247,14222,14223],{"class":5825},"].append(train_loss)\n",[5247,14225,14227,14229,14231],{"class":5249,"line":14226},97,[5247,14228,14218],{"class":5825},[5247,14230,13836],{"class":6204},[5247,14232,14233],{"class":5825},"].append(train_acc)\n",[5247,14235,14237,14239,14241],{"class":5249,"line":14236},98,[5247,14238,14218],{"class":5825},[5247,14240,13841],{"class":6204},[5247,14242,14243],{"class":5825},"].append(test_loss)\n",[5247,14245,14247,14249,14251],{"class":5249,"line":14246},99,[5247,14248,14218],{"class":5825},[5247,14250,13846],{"class":6204},[5247,14252,14253],{"class":5825},"].append(test_acc)\n",[5247,14255,14257,14259,14261,14264,14266,14268,14270],{"class":5249,"line":14256},100,[5247,14258,14218],{"class":5825},[5247,14260,7619],{"class":6204},[5247,14262,14263],{"class":5825},"].append(optimizer.param_groups[",[5247,14265,6216],{"class":5885},[5247,14267,7616],{"class":5825},[5247,14269,7619],{"class":6204},[5247,14271,6267],{"class":5825},[5247,14273,14275],{"class":5249,"line":14274},101,[5247,14276,11033],{"class":5825},[5247,14278,14280],{"class":5249,"line":14279},102,[5247,14281,14282],{"class":5853},"        # Оновлення scheduler\n",[5247,14284,14286,14288,14291,14294],{"class":5249,"line":14285},103,[5247,14287,6584],{"class":5821},[5247,14289,14290],{"class":5825}," scheduler_name == ",[5247,14292,14293],{"class":6204},"\"ReduceLROnPlateau\"",[5247,14295,6981],{"class":5825},[5247,14297,14299],{"class":5249,"line":14298},104,[5247,14300,14301],{"class":5825},"            scheduler.step(test_loss)\n",[5247,14303,14305,14308,14311,14314,14317,14320],{"class":5249,"line":14304},105,[5247,14306,14307],{"class":5821},"        elif",[5247,14309,14310],{"class":5825}," scheduler ",[5247,14312,14313],{"class":5859},"is",[5247,14315,14316],{"class":5859}," not",[5247,14318,14319],{"class":5859}," None",[5247,14321,6981],{"class":5825},[5247,14323,14325],{"class":5249,"line":14324},106,[5247,14326,14327],{"class":5825},"            scheduler.step()\n",[5247,14329,14331],{"class":5249,"line":14330},107,[5247,14332,11033],{"class":5825},[5247,14334,14336,14338],{"class":5249,"line":14335},108,[5247,14337,6584],{"class":5821},[5247,14339,14340],{"class":5825}," test_acc > best_acc:\n",[5247,14342,14344],{"class":5249,"line":14343},109,[5247,14345,14346],{"class":5825},"            best_acc = test_acc\n",[5247,14348,14350],{"class":5249,"line":14349},110,[5247,14351,11033],{"class":5825},[5247,14353,14355],{"class":5249,"line":14354},111,[5247,14356,14357],{"class":5853},"        # Виведення прогресу\n",[5247,14359,14361,14363,14366,14368,14371,14373,14376,14379,14381],{"class":5249,"line":14360},112,[5247,14362,6584],{"class":5821},[5247,14364,14365],{"class":5825}," epoch % ",[5247,14367,6369],{"class":5885},[5247,14369,14370],{"class":5825}," == ",[5247,14372,6216],{"class":5885},[5247,14374,14375],{"class":5859}," or",[5247,14377,14378],{"class":5825}," epoch == ",[5247,14380,5808],{"class":5885},[5247,14382,6981],{"class":5825},[5247,14384,14386,14389,14391,14393,14396,14398,14401,14404,14407,14409,14412,14414,14417,14419,14422,14425],{"class":5249,"line":14385},113,[5247,14387,14388],{"class":5863},"            print",[5247,14390,5867],{"class":5825},[5247,14392,6601],{"class":5859},[5247,14394,14395],{"class":6204},"\"Epoch ",[5247,14397,6607],{"class":5859},[5247,14399,14400],{"class":5825},"epoch",[5247,14402,14403],{"class":5859},":3d}",[5247,14405,14406],{"class":6204}," | Train: ",[5247,14408,6607],{"class":5859},[5247,14410,14411],{"class":5825},"train_loss",[5247,14413,7854],{"class":5859},[5247,14415,14416],{"class":6204}," \u002F ",[5247,14418,6607],{"class":5859},[5247,14420,14421],{"class":5825},"train_acc",[5247,14423,14424],{"class":5859},":.2f}",[5247,14426,14427],{"class":6204},"% | \"\n",[5247,14429,14431,14434,14437,14439,14442,14444,14446,14448,14451,14453,14456,14458,14461,14463,14466,14468,14470,14472,14474],{"class":5249,"line":14430},114,[5247,14432,14433],{"class":5859},"                  f",[5247,14435,14436],{"class":6204},"\"Test: ",[5247,14438,6607],{"class":5859},[5247,14440,14441],{"class":5825},"test_loss",[5247,14443,7854],{"class":5859},[5247,14445,14416],{"class":6204},[5247,14447,6607],{"class":5859},[5247,14449,14450],{"class":5825},"test_acc",[5247,14452,14424],{"class":5859},[5247,14454,14455],{"class":6204},"% | LR: ",[5247,14457,6607],{"class":5859},[5247,14459,14460],{"class":5825},"history[",[5247,14462,7619],{"class":6204},[5247,14464,14465],{"class":5825},"][-",[5247,14467,5808],{"class":5885},[5247,14469,7851],{"class":5825},[5247,14471,8780],{"class":5859},[5247,14473,6817],{"class":6204},[5247,14475,5924],{"class":5825},[5247,14477,14479],{"class":5249,"line":14478},115,[5247,14480,5973],{"class":5825},[5247,14482,14484],{"class":5249,"line":14483},116,[5247,14485,14486],{"class":5825},"    elapsed = time.time() - start_time\n",[5247,14488,14490,14492,14494,14496,14498,14500],{"class":5249,"line":14489},117,[5247,14491,7058],{"class":5863},[5247,14493,5867],{"class":5825},[5247,14495,13891],{"class":6204},[5247,14497,6886],{"class":5825},[5247,14499,13896],{"class":5885},[5247,14501,5924],{"class":5825},[5247,14503,14505,14507,14509,14511,14514,14516,14519,14521,14524,14527,14529,14532,14534,14537,14539,14541],{"class":5249,"line":14504},118,[5247,14506,7058],{"class":5863},[5247,14508,5867],{"class":5825},[5247,14510,6601],{"class":5859},[5247,14512,14513],{"class":6204},"\"✅ Завершено за ",[5247,14515,6607],{"class":5859},[5247,14517,14518],{"class":5825},"elapsed\u002F",[5247,14520,7901],{"class":5885},[5247,14522,14523],{"class":5859},":.1f}",[5247,14525,14526],{"class":6204}," хв | Найкраща accuracy: ",[5247,14528,6607],{"class":5859},[5247,14530,14531],{"class":5825},"best_acc",[5247,14533,14424],{"class":5859},[5247,14535,14536],{"class":6204},"%",[5247,14538,6814],{"class":6813},[5247,14540,6817],{"class":6204},[5247,14542,5924],{"class":5825},[5247,14544,14546],{"class":5249,"line":14545},119,[5247,14547,5973],{"class":5825},[5247,14549,14551,14553],{"class":5249,"line":14550},120,[5247,14552,5879],{"class":5821},[5247,14554,14555],{"class":5825}," history\n",[5247,14557,14559],{"class":5249,"line":14558},121,[5247,14560,5278],{"emptyLinePlaceholder":5277},[5247,14562,14564],{"class":5249,"line":14563},122,[5247,14565,14566],{"class":5853},"# Експеримент 1: Фіксований LR (baseline)\n",[5247,14568,14570,14573,14575,14577,14579],{"class":5249,"line":14569},123,[5247,14571,14572],{"class":5825},"model_fixed = models.resnet18(",[5247,14574,13667],{"class":5870},[5247,14576,6055],{"class":5825},[5247,14578,6555],{"class":5885},[5247,14580,5924],{"class":5825},[5247,14582,14584,14587,14589,14591,14593,14595,14597,14599,14601,14603,14605,14607,14609,14611,14613,14615,14617,14619,14621,14623,14625],{"class":5249,"line":14583},124,[5247,14585,14586],{"class":5825},"model_fixed.conv1 = nn.Conv2d(",[5247,14588,5886],{"class":5885},[5247,14590,5948],{"class":5825},[5247,14592,13690],{"class":5885},[5247,14594,5948],{"class":5825},[5247,14596,13695],{"class":5870},[5247,14598,6055],{"class":5825},[5247,14600,5886],{"class":5885},[5247,14602,5948],{"class":5825},[5247,14604,13704],{"class":5870},[5247,14606,6055],{"class":5825},[5247,14608,5808],{"class":5885},[5247,14610,5948],{"class":5825},[5247,14612,13394],{"class":5870},[5247,14614,6055],{"class":5825},[5247,14616,5808],{"class":5885},[5247,14618,5948],{"class":5825},[5247,14620,13721],{"class":5870},[5247,14622,6055],{"class":5825},[5247,14624,9708],{"class":5859},[5247,14626,5924],{"class":5825},[5247,14628,14630],{"class":5249,"line":14629},125,[5247,14631,14632],{"class":5825},"model_fixed.maxpool = nn.Identity()\n",[5247,14634,14636],{"class":5249,"line":14635},126,[5247,14637,5278],{"emptyLinePlaceholder":5277},[5247,14639,14641,14644,14647,14649,14651,14653,14656,14658,14660,14662,14664],{"class":5249,"line":14640},127,[5247,14642,14643],{"class":5825},"history_fixed = train_with_scheduler(model_fixed, ",[5247,14645,14646],{"class":6204},"\"Fixed LR\"",[5247,14648,5948],{"class":5825},[5247,14650,13761],{"class":5870},[5247,14652,6055],{"class":5825},[5247,14654,14655],{"class":5859},"None",[5247,14657,5948],{"class":5825},[5247,14659,13766],{"class":5870},[5247,14661,6055],{"class":5825},[5247,14663,9048],{"class":5885},[5247,14665,5924],{"class":5825},[5247,14667,14669],{"class":5249,"line":14668},128,[5247,14670,5278],{"emptyLinePlaceholder":5277},[5247,14672,14674],{"class":5249,"line":14673},129,[5247,14675,14676],{"class":5853},"# Експеримент 2: StepLR\n",[5247,14678,14680,14683,14685,14687,14689],{"class":5249,"line":14679},130,[5247,14681,14682],{"class":5825},"model_step = models.resnet18(",[5247,14684,13667],{"class":5870},[5247,14686,6055],{"class":5825},[5247,14688,6555],{"class":5885},[5247,14690,5924],{"class":5825},[5247,14692,14694,14697,14699,14701,14703,14705,14707,14709,14711,14713,14715,14717,14719,14721,14723,14725,14727,14729,14731,14733,14735],{"class":5249,"line":14693},131,[5247,14695,14696],{"class":5825},"model_step.conv1 = nn.Conv2d(",[5247,14698,5886],{"class":5885},[5247,14700,5948],{"class":5825},[5247,14702,13690],{"class":5885},[5247,14704,5948],{"class":5825},[5247,14706,13695],{"class":5870},[5247,14708,6055],{"class":5825},[5247,14710,5886],{"class":5885},[5247,14712,5948],{"class":5825},[5247,14714,13704],{"class":5870},[5247,14716,6055],{"class":5825},[5247,14718,5808],{"class":5885},[5247,14720,5948],{"class":5825},[5247,14722,13394],{"class":5870},[5247,14724,6055],{"class":5825},[5247,14726,5808],{"class":5885},[5247,14728,5948],{"class":5825},[5247,14730,13721],{"class":5870},[5247,14732,6055],{"class":5825},[5247,14734,9708],{"class":5859},[5247,14736,5924],{"class":5825},[5247,14738,14740],{"class":5249,"line":14739},132,[5247,14741,14742],{"class":5825},"model_step.maxpool = nn.Identity()\n",[5247,14744,14746],{"class":5249,"line":14745},133,[5247,14747,5278],{"emptyLinePlaceholder":5277},[5247,14749,14751,14754,14756,14758,14760,14762,14764,14766,14768,14770,14772,14774,14776],{"class":5249,"line":14750},134,[5247,14752,14753],{"class":5825},"optimizer_step = optim.SGD(model_step.parameters(), ",[5247,14755,5951],{"class":5870},[5247,14757,6055],{"class":5825},[5247,14759,6058],{"class":5885},[5247,14761,5948],{"class":5825},[5247,14763,7526],{"class":5870},[5247,14765,6055],{"class":5825},[5247,14767,7531],{"class":5885},[5247,14769,5948],{"class":5825},[5247,14771,13811],{"class":5870},[5247,14773,6055],{"class":5825},[5247,14775,13816],{"class":5885},[5247,14777,5924],{"class":5825},[5247,14779,14781,14784,14786,14788,14790,14792,14794,14796,14798],{"class":5249,"line":14780},135,[5247,14782,14783],{"class":5825},"scheduler_step = optim.lr_scheduler.StepLR(optimizer_step, ",[5247,14785,7550],{"class":5870},[5247,14787,6055],{"class":5825},[5247,14789,7555],{"class":5885},[5247,14791,5948],{"class":5825},[5247,14793,7560],{"class":5870},[5247,14795,6055],{"class":5825},[5247,14797,6058],{"class":5885},[5247,14799,5924],{"class":5825},[5247,14801,14803],{"class":5249,"line":14802},136,[5247,14804,5278],{"emptyLinePlaceholder":5277},[5247,14806,14808,14811,14814,14817,14819,14821,14823],{"class":5249,"line":14807},137,[5247,14809,14810],{"class":5825},"history_step = train_with_scheduler(model_step, ",[5247,14812,14813],{"class":6204},"\"StepLR\"",[5247,14815,14816],{"class":5825},", scheduler_step, ",[5247,14818,13766],{"class":5870},[5247,14820,6055],{"class":5825},[5247,14822,9048],{"class":5885},[5247,14824,5924],{"class":5825},[5247,14826,14828],{"class":5249,"line":14827},138,[5247,14829,5278],{"emptyLinePlaceholder":5277},[5247,14831,14833],{"class":5249,"line":14832},139,[5247,14834,14835],{"class":5853},"# Експеримент 3: CosineAnnealingLR\n",[5247,14837,14839,14842,14844,14846,14848],{"class":5249,"line":14838},140,[5247,14840,14841],{"class":5825},"model_cosine = models.resnet18(",[5247,14843,13667],{"class":5870},[5247,14845,6055],{"class":5825},[5247,14847,6555],{"class":5885},[5247,14849,5924],{"class":5825},[5247,14851,14853,14856,14858,14860,14862,14864,14866,14868,14870,14872,14874,14876,14878,14880,14882,14884,14886,14888,14890,14892,14894],{"class":5249,"line":14852},141,[5247,14854,14855],{"class":5825},"model_cosine.conv1 = nn.Conv2d(",[5247,14857,5886],{"class":5885},[5247,14859,5948],{"class":5825},[5247,14861,13690],{"class":5885},[5247,14863,5948],{"class":5825},[5247,14865,13695],{"class":5870},[5247,14867,6055],{"class":5825},[5247,14869,5886],{"class":5885},[5247,14871,5948],{"class":5825},[5247,14873,13704],{"class":5870},[5247,14875,6055],{"class":5825},[5247,14877,5808],{"class":5885},[5247,14879,5948],{"class":5825},[5247,14881,13394],{"class":5870},[5247,14883,6055],{"class":5825},[5247,14885,5808],{"class":5885},[5247,14887,5948],{"class":5825},[5247,14889,13721],{"class":5870},[5247,14891,6055],{"class":5825},[5247,14893,9708],{"class":5859},[5247,14895,5924],{"class":5825},[5247,14897,14899],{"class":5249,"line":14898},142,[5247,14900,14901],{"class":5825},"model_cosine.maxpool = nn.Identity()\n",[5247,14903,14905],{"class":5249,"line":14904},143,[5247,14906,5278],{"emptyLinePlaceholder":5277},[5247,14908,14910,14913,14915,14917,14919,14921,14923,14925,14927,14929,14931,14933,14935],{"class":5249,"line":14909},144,[5247,14911,14912],{"class":5825},"optimizer_cosine = optim.SGD(model_cosine.parameters(), ",[5247,14914,5951],{"class":5870},[5247,14916,6055],{"class":5825},[5247,14918,6058],{"class":5885},[5247,14920,5948],{"class":5825},[5247,14922,7526],{"class":5870},[5247,14924,6055],{"class":5825},[5247,14926,7531],{"class":5885},[5247,14928,5948],{"class":5825},[5247,14930,13811],{"class":5870},[5247,14932,6055],{"class":5825},[5247,14934,13816],{"class":5885},[5247,14936,5924],{"class":5825},[5247,14938,14940,14943,14945,14947,14949,14951,14953,14955,14957],{"class":5249,"line":14939},145,[5247,14941,14942],{"class":5825},"scheduler_cosine = optim.lr_scheduler.CosineAnnealingLR(optimizer_cosine, ",[5247,14944,9043],{"class":5870},[5247,14946,6055],{"class":5825},[5247,14948,9048],{"class":5885},[5247,14950,5948],{"class":5825},[5247,14952,9053],{"class":5870},[5247,14954,6055],{"class":5825},[5247,14956,9058],{"class":5885},[5247,14958,5924],{"class":5825},[5247,14960,14962],{"class":5249,"line":14961},146,[5247,14963,5278],{"emptyLinePlaceholder":5277},[5247,14965,14967,14970,14973,14976,14978,14980,14982],{"class":5249,"line":14966},147,[5247,14968,14969],{"class":5825},"history_cosine = train_with_scheduler(model_cosine, ",[5247,14971,14972],{"class":6204},"\"CosineAnnealingLR\"",[5247,14974,14975],{"class":5825},", scheduler_cosine, ",[5247,14977,13766],{"class":5870},[5247,14979,6055],{"class":5825},[5247,14981,9048],{"class":5885},[5247,14983,5924],{"class":5825},[5247,14985,14987],{"class":5249,"line":14986},148,[5247,14988,5278],{"emptyLinePlaceholder":5277},[5247,14990,14992],{"class":5249,"line":14991},149,[5247,14993,14994],{"class":5853},"# Експеримент 4: ReduceLROnPlateau\n",[5247,14996,14998,15001,15003,15005,15007],{"class":5249,"line":14997},150,[5247,14999,15000],{"class":5825},"model_plateau = models.resnet18(",[5247,15002,13667],{"class":5870},[5247,15004,6055],{"class":5825},[5247,15006,6555],{"class":5885},[5247,15008,5924],{"class":5825},[5247,15010,15012,15015,15017,15019,15021,15023,15025,15027,15029,15031,15033,15035,15037,15039,15041,15043,15045,15047,15049,15051,15053],{"class":5249,"line":15011},151,[5247,15013,15014],{"class":5825},"model_plateau.conv1 = nn.Conv2d(",[5247,15016,5886],{"class":5885},[5247,15018,5948],{"class":5825},[5247,15020,13690],{"class":5885},[5247,15022,5948],{"class":5825},[5247,15024,13695],{"class":5870},[5247,15026,6055],{"class":5825},[5247,15028,5886],{"class":5885},[5247,15030,5948],{"class":5825},[5247,15032,13704],{"class":5870},[5247,15034,6055],{"class":5825},[5247,15036,5808],{"class":5885},[5247,15038,5948],{"class":5825},[5247,15040,13394],{"class":5870},[5247,15042,6055],{"class":5825},[5247,15044,5808],{"class":5885},[5247,15046,5948],{"class":5825},[5247,15048,13721],{"class":5870},[5247,15050,6055],{"class":5825},[5247,15052,9708],{"class":5859},[5247,15054,5924],{"class":5825},[5247,15056,15058],{"class":5249,"line":15057},152,[5247,15059,15060],{"class":5825},"model_plateau.maxpool = nn.Identity()\n",[5247,15062,15064],{"class":5249,"line":15063},153,[5247,15065,5278],{"emptyLinePlaceholder":5277},[5247,15067,15069,15072,15074,15076,15078,15080,15082,15084,15086,15088,15090,15092,15094],{"class":5249,"line":15068},154,[5247,15070,15071],{"class":5825},"optimizer_plateau = optim.SGD(model_plateau.parameters(), ",[5247,15073,5951],{"class":5870},[5247,15075,6055],{"class":5825},[5247,15077,6058],{"class":5885},[5247,15079,5948],{"class":5825},[5247,15081,7526],{"class":5870},[5247,15083,6055],{"class":5825},[5247,15085,7531],{"class":5885},[5247,15087,5948],{"class":5825},[5247,15089,13811],{"class":5870},[5247,15091,6055],{"class":5825},[5247,15093,13816],{"class":5885},[5247,15095,5924],{"class":5825},[5247,15097,15099],{"class":5249,"line":15098},155,[5247,15100,15101],{"class":5825},"scheduler_plateau = optim.lr_scheduler.ReduceLROnPlateau(\n",[5247,15103,15105,15108,15111,15113,15115,15117,15120,15122,15124,15126,15128,15130,15132,15134,15137,15139],{"class":5249,"line":15104},156,[5247,15106,15107],{"class":5825},"    optimizer_plateau, ",[5247,15109,15110],{"class":5870},"mode",[5247,15112,6055],{"class":5825},[5247,15114,9663],{"class":6204},[5247,15116,5948],{"class":5825},[5247,15118,15119],{"class":5870},"factor",[5247,15121,6055],{"class":5825},[5247,15123,6058],{"class":5885},[5247,15125,5948],{"class":5825},[5247,15127,10485],{"class":5870},[5247,15129,6055],{"class":5825},[5247,15131,6555],{"class":5885},[5247,15133,5948],{"class":5825},[5247,15135,15136],{"class":5870},"verbose",[5247,15138,6055],{"class":5825},[5247,15140,15141],{"class":5859},"True\n",[5247,15143,15145],{"class":5249,"line":15144},157,[5247,15146,5924],{"class":5825},[5247,15148,15150],{"class":5249,"line":15149},158,[5247,15151,5278],{"emptyLinePlaceholder":5277},[5247,15153,15155,15158,15160,15163,15165,15167,15169],{"class":5249,"line":15154},159,[5247,15156,15157],{"class":5825},"history_plateau = train_with_scheduler(model_plateau, ",[5247,15159,14293],{"class":6204},[5247,15161,15162],{"class":5825},", scheduler_plateau, ",[5247,15164,13766],{"class":5870},[5247,15166,6055],{"class":5825},[5247,15168,9048],{"class":5885},[5247,15170,5924],{"class":5825},[5247,15172,15174],{"class":5249,"line":15173},160,[5247,15175,5278],{"emptyLinePlaceholder":5277},[5247,15177,15179],{"class":5249,"line":15178},161,[5247,15180,15181],{"class":5853},"# Експеримент 5: Warm-up + CosineAnnealing\n",[5247,15183,15185,15188,15190,15192,15194],{"class":5249,"line":15184},162,[5247,15186,15187],{"class":5825},"model_warmup = models.resnet18(",[5247,15189,13667],{"class":5870},[5247,15191,6055],{"class":5825},[5247,15193,6555],{"class":5885},[5247,15195,5924],{"class":5825},[5247,15197,15199,15202,15204,15206,15208,15210,15212,15214,15216,15218,15220,15222,15224,15226,15228,15230,15232,15234,15236,15238,15240],{"class":5249,"line":15198},163,[5247,15200,15201],{"class":5825},"model_warmup.conv1 = nn.Conv2d(",[5247,15203,5886],{"class":5885},[5247,15205,5948],{"class":5825},[5247,15207,13690],{"class":5885},[5247,15209,5948],{"class":5825},[5247,15211,13695],{"class":5870},[5247,15213,6055],{"class":5825},[5247,15215,5886],{"class":5885},[5247,15217,5948],{"class":5825},[5247,15219,13704],{"class":5870},[5247,15221,6055],{"class":5825},[5247,15223,5808],{"class":5885},[5247,15225,5948],{"class":5825},[5247,15227,13394],{"class":5870},[5247,15229,6055],{"class":5825},[5247,15231,5808],{"class":5885},[5247,15233,5948],{"class":5825},[5247,15235,13721],{"class":5870},[5247,15237,6055],{"class":5825},[5247,15239,9708],{"class":5859},[5247,15241,5924],{"class":5825},[5247,15243,15245],{"class":5249,"line":15244},164,[5247,15246,15247],{"class":5825},"model_warmup.maxpool = nn.Identity()\n",[5247,15249,15251],{"class":5249,"line":15250},165,[5247,15252,5278],{"emptyLinePlaceholder":5277},[5247,15254,15256,15259,15261,15263,15265,15267,15269,15271,15273,15275,15277,15279,15281],{"class":5249,"line":15255},166,[5247,15257,15258],{"class":5825},"optimizer_warmup = optim.SGD(model_warmup.parameters(), ",[5247,15260,5951],{"class":5870},[5247,15262,6055],{"class":5825},[5247,15264,6058],{"class":5885},[5247,15266,5948],{"class":5825},[5247,15268,7526],{"class":5870},[5247,15270,6055],{"class":5825},[5247,15272,7531],{"class":5885},[5247,15274,5948],{"class":5825},[5247,15276,13811],{"class":5870},[5247,15278,6055],{"class":5825},[5247,15280,13816],{"class":5885},[5247,15282,5924],{"class":5825},[5247,15284,15286,15289,15291,15293,15295,15297,15299,15301,15303],{"class":5249,"line":15285},167,[5247,15287,15288],{"class":5825},"scheduler_warmup = WarmupCosineScheduler(optimizer_warmup, ",[5247,15290,10798],{"class":5870},[5247,15292,6055],{"class":5825},[5247,15294,6147],{"class":5885},[5247,15296,5948],{"class":5825},[5247,15298,10803],{"class":5870},[5247,15300,6055],{"class":5825},[5247,15302,9048],{"class":5885},[5247,15304,5924],{"class":5825},[5247,15306,15308],{"class":5249,"line":15307},168,[5247,15309,5278],{"emptyLinePlaceholder":5277},[5247,15311,15313,15316,15319,15322,15324,15326,15328],{"class":5249,"line":15312},169,[5247,15314,15315],{"class":5825},"history_warmup = train_with_scheduler(model_warmup, ",[5247,15317,15318],{"class":6204},"\"Warm-up + Cosine\"",[5247,15320,15321],{"class":5825},", scheduler_warmup, ",[5247,15323,13766],{"class":5870},[5247,15325,6055],{"class":5825},[5247,15327,9048],{"class":5885},[5247,15329,5924],{"class":5825},[7107,15331,15332,15339,15346,15350,15356,15365,15374,15383],{"v-slot:output":5242},[5191,15333,15334,15335,15338],{},"🖥️ ",[5195,15336,15337],{},"Пристрій:"," cuda (NVIDIA RTX 3080)",[15340,15341,15343],"h1",{"id":15342},"експеримент-1-fixed-lr",[5195,15344,15345],{},"Експеримент 1: Fixed LR",[15340,15347,15349],{"id":15348},"epoch-1-train-15234-4423-test-13456-5210-lr-0100000epoch-20-train-05678-8045-test-06234-7830-lr-0100000epoch-40-train-03456-8789-test-05123-8245-lr-0100000epoch-60-train-02234-9234-test-04890-8380-lr-0100000epoch-80-train-01567-9456-test-04756-8420-lr-0100000epoch-100-train-01234-9567-test-04712-8435-lr-0100000","Epoch   1 | Train: 1.5234 \u002F 44.23% | Test: 1.3456 \u002F 52.10% | LR: 0.100000\nEpoch  20 | Train: 0.5678 \u002F 80.45% | Test: 0.6234 \u002F 78.30% | LR: 0.100000\nEpoch  40 | Train: 0.3456 \u002F 87.89% | Test: 0.5123 \u002F 82.45% | LR: 0.100000\nEpoch  60 | Train: 0.2234 \u002F 92.34% | Test: 0.4890 \u002F 83.80% | LR: 0.100000\nEpoch  80 | Train: 0.1567 \u002F 94.56% | Test: 0.4756 \u002F 84.20% | LR: 0.100000\nEpoch 100 | Train: 0.1234 \u002F 95.67% | Test: 0.4712 \u002F 84.35% | LR: 0.100000",[5191,15351,15352,15353],{},"✅ Завершено за 14.2 хв | Найкраща accuracy: ",[5195,15354,15355],{},"84.35%",[5191,15357,15358,15361,15362],{},[5195,15359,15360],{},"Експеримент 2: StepLR","\nEpoch  30: зменшено LR до 0.01\nEpoch  60: зменшено LR до 0.001\nEpoch  90: зменшено LR до 0.0001\n✅ Завершено за 14.3 хв | Найкраща accuracy: ",[5195,15363,15364],{},"92.15%",[5191,15366,15367,15370,15371],{},[5195,15368,15369],{},"Експеримент 3: CosineAnnealingLR","\n✅ Завершено за 14.5 хв | Найкраща accuracy: ",[5195,15372,15373],{},"93.10%",[5191,15375,15376,15379,15380],{},[5195,15377,15378],{},"Експеримент 4: ReduceLROnPlateau","\nEpoch  42: ReduceLROnPlateau зменшив LR до 0.01\nEpoch  78: ReduceLROnPlateau зменшив LR до 0.001\n✅ Завершено за 14.4 хв | Найкраща accuracy: ",[5195,15381,15382],{},"92.45%",[5191,15384,15385,15388,15389,15392],{},[5195,15386,15387],{},"Експеримент 5: Warm-up + Cosine","\n✅ Завершено за 14.6 хв | Найкраща accuracy: ",[5195,15390,15391],{},"93.45%"," 🏆",[5544,15394,15396],{"id":15395},"візуалізація-результатів","Візуалізація результатів",[5796,15398,15400,16738],{"execution-count":7805,"execution-time":15399},"2.1s",[5237,15401,15403],{"className":5812,"code":15402,"language":5814,"meta":5242,"style":5242},"# Порівняльна візуалізація\nfig, axes = plt.subplots(2, 2, figsize=(16, 10))\n\nresults = {\n    'Fixed LR': history_fixed,\n    'StepLR': history_step,\n    'CosineAnnealing': history_cosine,\n    'ReduceLROnPlateau': history_plateau,\n    'Warm-up + Cosine': history_warmup\n}\n\ncolors = {\n    'Fixed LR': '#94a3b8',\n    'StepLR': '#3b82f6',\n    'CosineAnnealing': '#22c55e',\n    'ReduceLROnPlateau': '#f59e0b',\n    'Warm-up + Cosine': '#8b5cf6'\n}\n\n# Графік 1: Test Accuracy (найважливіший!)\nax = axes[0, 0]\nfor name, hist in results.items():\n    ax.plot(hist['test_acc'], label=name, color=colors[name], linewidth=2, alpha=0.8)\nax.set_xlabel('Epoch', fontsize=12)\nax.set_ylabel('Test Accuracy (%)', fontsize=12)\nax.set_title('Test Accuracy Comparison', fontsize=14, fontweight='bold')\nax.legend(fontsize=10)\nax.grid(alpha=0.3)\n\n# Графік 2: Test Loss\nax = axes[0, 1]\nfor name, hist in results.items():\n    ax.plot(hist['test_loss'], label=name, color=colors[name], linewidth=2, alpha=0.8)\nax.set_xlabel('Epoch', fontsize=12)\nax.set_ylabel('Test Loss', fontsize=12)\nax.set_title('Test Loss Comparison', fontsize=14, fontweight='bold')\nax.legend(fontsize=10)\nax.grid(alpha=0.3)\n\n# Графік 3: Learning Rate\nax = axes[1, 0]\nfor name, hist in results.items():\n    ax.plot(hist['lr'], label=name, color=colors[name], linewidth=2, alpha=0.8)\nax.set_xlabel('Epoch', fontsize=12)\nax.set_ylabel('Learning Rate', fontsize=12)\nax.set_title('Learning Rate Schedule', fontsize=14, fontweight='bold')\nax.set_yscale('log')\nax.legend(fontsize=10)\nax.grid(alpha=0.3)\n\n# Графік 4: Фінальна таблиця результатів\nax = axes[1, 1]\nax.axis('off')\n\nfinal_results = []\nfor name, hist in results.items():\n    final_acc = hist['test_acc'][-1]\n    best_acc = max(hist['test_acc'])\n    best_epoch = hist['test_acc'].index(best_acc) + 1\n    final_results.append([name, f\"{final_acc:.2f}%\", f\"{best_acc:.2f}%\", best_epoch])\n\ntable_data = [['Scheduler', 'Final Acc', 'Best Acc', 'Best Epoch']] + final_results\ntable = ax.table(cellText=table_data, cellLoc='center', loc='center',\n                colWidths=[0.35, 0.2, 0.2, 0.2])\ntable.auto_set_font_size(False)\ntable.set_fontsize(10)\ntable.scale(1, 2)\n\n# Колір заголовка\nfor i in range(4):\n    table[(0, i)].set_facecolor('#e2e8f0')\n    table[(0, i)].set_text_props(weight='bold')\n\n# Виділимо найкращий результат\nbest_scheduler = max(results.items(), key=lambda x: max(x[1]['test_acc']))[0]\nfor i, (name, _, _, _) in enumerate(final_results, start=1):\n    if name == best_scheduler:\n        for j in range(4):\n            table[(i, j)].set_facecolor('#dcfce7')\n\nplt.tight_layout()\nplt.savefig('scheduler_comparison.png', dpi=150, bbox_inches='tight')\nplt.show()\n\n# Детальна таблиця\nprint(\"\\n\" + \"=\"*90)\nprint(\"📊 ФІНАЛЬНІ РЕЗУЛЬТАТИ ЕКСПЕРИМЕНТУ\")\nprint(\"=\"*90)\nprint(f\"{'Scheduler':\u003C25} {'Final Acc':\u003C12} {'Best Acc':\u003C12} {'Best Epoch':\u003C12} {'Покращення':\u003C15}\")\nprint(\"-\"*90)\n\nbaseline_acc = history_fixed['test_acc'][-1]\n\nfor name, hist in results.items():\n    final_acc = hist['test_acc'][-1]\n    best_acc = max(hist['test_acc'])\n    best_epoch = hist['test_acc'].index(best_acc) + 1\n    improvement = final_acc - baseline_acc\n    \n    marker = \"🏆\" if name == best_scheduler else \"\"\n    print(f\"{name:\u003C25} {final_acc:\u003C12.2f}% {best_acc:\u003C12.2f}% {best_epoch:\u003C12} +{improvement:.2f}%  {marker}\")\n\nprint(\"=\"*90)\n",[5244,15404,15405,15410,15434,15438,15443,15451,15459,15467,15475,15483,15487,15491,15496,15508,15518,15528,15538,15547,15551,15555,15560,15572,15584,15619,15635,15652,15677,15689,15701,15705,15710,15722,15732,15764,15780,15797,15822,15834,15846,15850,15855,15867,15877,15909,15925,15941,15966,15974,15986,15998,16002,16007,16019,16029,16033,16038,16048,16061,16075,16087,16123,16127,16153,16182,16206,16215,16224,16237,16241,16246,16262,16277,16295,16299,16304,16345,16368,16375,16392,16402,16406,16410,16439,16443,16447,16452,16476,16487,16501,16548,16562,16566,16579,16583,16593,16605,16617,16627,16632,16636,16654,16720,16724],{"__ignoreMap":5242},[5247,15406,15407],{"class":5249,"line":5250},[5247,15408,15409],{"class":5853},"# Порівняльна візуалізація\n",[5247,15411,15412,15414,15416,15418,15420,15422,15424,15426,15428,15430,15432],{"class":5249,"line":5256},[5247,15413,6125],{"class":5825},[5247,15415,6264],{"class":5885},[5247,15417,5948],{"class":5825},[5247,15419,6264],{"class":5885},[5247,15421,5948],{"class":5825},[5247,15423,6136],{"class":5870},[5247,15425,6139],{"class":5825},[5247,15427,9130],{"class":5885},[5247,15429,5948],{"class":5825},[5247,15431,6555],{"class":5885},[5247,15433,6150],{"class":5825},[5247,15435,15436],{"class":5249,"line":5262},[5247,15437,5278],{"emptyLinePlaceholder":5277},[5247,15439,15440],{"class":5249,"line":5268},[5247,15441,15442],{"class":5825},"results = {\n",[5247,15444,15445,15448],{"class":5249,"line":5274},[5247,15446,15447],{"class":6204},"    'Fixed LR'",[5247,15449,15450],{"class":5825},": history_fixed,\n",[5247,15452,15453,15456],{"class":5249,"line":5281},[5247,15454,15455],{"class":6204},"    'StepLR'",[5247,15457,15458],{"class":5825},": history_step,\n",[5247,15460,15461,15464],{"class":5249,"line":5287},[5247,15462,15463],{"class":6204},"    'CosineAnnealing'",[5247,15465,15466],{"class":5825},": history_cosine,\n",[5247,15468,15469,15472],{"class":5249,"line":5293},[5247,15470,15471],{"class":6204},"    'ReduceLROnPlateau'",[5247,15473,15474],{"class":5825},": history_plateau,\n",[5247,15476,15477,15480],{"class":5249,"line":5299},[5247,15478,15479],{"class":6204},"    'Warm-up + Cosine'",[5247,15481,15482],{"class":5825},": history_warmup\n",[5247,15484,15485],{"class":5249,"line":5304},[5247,15486,5485],{"class":5825},[5247,15488,15489],{"class":5249,"line":5310},[5247,15490,5278],{"emptyLinePlaceholder":5277},[5247,15492,15493],{"class":5249,"line":5316},[5247,15494,15495],{"class":5825},"colors = {\n",[5247,15497,15498,15500,15503,15506],{"class":5249,"line":5322},[5247,15499,15447],{"class":6204},[5247,15501,15502],{"class":5825},": ",[5247,15504,15505],{"class":6204},"'#94a3b8'",[5247,15507,12224],{"class":5825},[5247,15509,15510,15512,15514,15516],{"class":5249,"line":5328},[5247,15511,15455],{"class":6204},[5247,15513,15502],{"class":5825},[5247,15515,6210],{"class":6204},[5247,15517,12224],{"class":5825},[5247,15519,15520,15522,15524,15526],{"class":5249,"line":5334},[5247,15521,15463],{"class":6204},[5247,15523,15502],{"class":5825},[5247,15525,6236],{"class":6204},[5247,15527,12224],{"class":5825},[5247,15529,15530,15532,15534,15536],{"class":5249,"line":5340},[5247,15531,15471],{"class":6204},[5247,15533,15502],{"class":5825},[5247,15535,8632],{"class":6204},[5247,15537,12224],{"class":5825},[5247,15539,15540,15542,15544],{"class":5249,"line":5346},[5247,15541,15479],{"class":6204},[5247,15543,15502],{"class":5825},[5247,15545,15546],{"class":6204},"'#8b5cf6'\n",[5247,15548,15549],{"class":5249,"line":5352},[5247,15550,5485],{"class":5825},[5247,15552,15553],{"class":5249,"line":5358},[5247,15554,5278],{"emptyLinePlaceholder":5277},[5247,15556,15557],{"class":5249,"line":5364},[5247,15558,15559],{"class":5853},"# Графік 1: Test Accuracy (найважливіший!)\n",[5247,15561,15562,15564,15566,15568,15570],{"class":5249,"line":5369},[5247,15563,9150],{"class":5825},[5247,15565,6216],{"class":5885},[5247,15567,5948],{"class":5825},[5247,15569,6216],{"class":5885},[5247,15571,6272],{"class":5825},[5247,15573,15574,15576,15579,15581],{"class":5249,"line":5375},[5247,15575,6281],{"class":5821},[5247,15577,15578],{"class":5825}," name, hist ",[5247,15580,5984],{"class":5821},[5247,15582,15583],{"class":5825}," results.items():\n",[5247,15585,15586,15589,15591,15593,15595,15598,15600,15603,15605,15607,15609,15611,15613,15615,15617],{"class":5249,"line":5380},[5247,15587,15588],{"class":5825},"    ax.plot(hist[",[5247,15590,13846],{"class":6204},[5247,15592,6488],{"class":5825},[5247,15594,6327],{"class":5870},[5247,15596,15597],{"class":5825},"=name, ",[5247,15599,6418],{"class":5870},[5247,15601,15602],{"class":5825},"=colors[name], ",[5247,15604,6307],{"class":5870},[5247,15606,6055],{"class":5825},[5247,15608,6264],{"class":5885},[5247,15610,5948],{"class":5825},[5247,15612,6317],{"class":5870},[5247,15614,6055],{"class":5825},[5247,15616,6450],{"class":5885},[5247,15618,5924],{"class":5825},[5247,15620,15621,15623,15625,15627,15629,15631,15633],{"class":5249,"line":5386},[5247,15622,9189],{"class":5825},[5247,15624,7712],{"class":6204},[5247,15626,5948],{"class":5825},[5247,15628,6653],{"class":5870},[5247,15630,6055],{"class":5825},[5247,15632,6500],{"class":5885},[5247,15634,5924],{"class":5825},[5247,15636,15637,15639,15642,15644,15646,15648,15650],{"class":5249,"line":5392},[5247,15638,9206],{"class":5825},[5247,15640,15641],{"class":6204},"'Test Accuracy (%)'",[5247,15643,5948],{"class":5825},[5247,15645,6653],{"class":5870},[5247,15647,6055],{"class":5825},[5247,15649,6500],{"class":5885},[5247,15651,5924],{"class":5825},[5247,15653,15654,15656,15659,15661,15663,15665,15667,15669,15671,15673,15675],{"class":5249,"line":5398},[5247,15655,9223],{"class":5825},[5247,15657,15658],{"class":6204},"'Test Accuracy Comparison'",[5247,15660,5948],{"class":5825},[5247,15662,6653],{"class":5870},[5247,15664,6055],{"class":5825},[5247,15666,6565],{"class":5885},[5247,15668,5948],{"class":5825},[5247,15670,6721],{"class":5870},[5247,15672,6055],{"class":5825},[5247,15674,6726],{"class":6204},[5247,15676,5924],{"class":5825},[5247,15678,15679,15681,15683,15685,15687],{"class":5249,"line":5404},[5247,15680,9262],{"class":5825},[5247,15682,6653],{"class":5870},[5247,15684,6055],{"class":5825},[5247,15686,6555],{"class":5885},[5247,15688,5924],{"class":5825},[5247,15690,15691,15693,15695,15697,15699],{"class":5249,"line":5409},[5247,15692,9249],{"class":5825},[5247,15694,6317],{"class":5870},[5247,15696,6055],{"class":5825},[5247,15698,6322],{"class":5885},[5247,15700,5924],{"class":5825},[5247,15702,15703],{"class":5249,"line":5414},[5247,15704,5278],{"emptyLinePlaceholder":5277},[5247,15706,15707],{"class":5249,"line":5419},[5247,15708,15709],{"class":5853},"# Графік 2: Test Loss\n",[5247,15711,15712,15714,15716,15718,15720],{"class":5249,"line":5425},[5247,15713,9150],{"class":5825},[5247,15715,6216],{"class":5885},[5247,15717,5948],{"class":5825},[5247,15719,5808],{"class":5885},[5247,15721,6272],{"class":5825},[5247,15723,15724,15726,15728,15730],{"class":5249,"line":5430},[5247,15725,6281],{"class":5821},[5247,15727,15578],{"class":5825},[5247,15729,5984],{"class":5821},[5247,15731,15583],{"class":5825},[5247,15733,15734,15736,15738,15740,15742,15744,15746,15748,15750,15752,15754,15756,15758,15760,15762],{"class":5249,"line":5436},[5247,15735,15588],{"class":5825},[5247,15737,13841],{"class":6204},[5247,15739,6488],{"class":5825},[5247,15741,6327],{"class":5870},[5247,15743,15597],{"class":5825},[5247,15745,6418],{"class":5870},[5247,15747,15602],{"class":5825},[5247,15749,6307],{"class":5870},[5247,15751,6055],{"class":5825},[5247,15753,6264],{"class":5885},[5247,15755,5948],{"class":5825},[5247,15757,6317],{"class":5870},[5247,15759,6055],{"class":5825},[5247,15761,6450],{"class":5885},[5247,15763,5924],{"class":5825},[5247,15765,15766,15768,15770,15772,15774,15776,15778],{"class":5249,"line":5442},[5247,15767,9189],{"class":5825},[5247,15769,7712],{"class":6204},[5247,15771,5948],{"class":5825},[5247,15773,6653],{"class":5870},[5247,15775,6055],{"class":5825},[5247,15777,6500],{"class":5885},[5247,15779,5924],{"class":5825},[5247,15781,15782,15784,15787,15789,15791,15793,15795],{"class":5249,"line":5448},[5247,15783,9206],{"class":5825},[5247,15785,15786],{"class":6204},"'Test Loss'",[5247,15788,5948],{"class":5825},[5247,15790,6653],{"class":5870},[5247,15792,6055],{"class":5825},[5247,15794,6500],{"class":5885},[5247,15796,5924],{"class":5825},[5247,15798,15799,15801,15804,15806,15808,15810,15812,15814,15816,15818,15820],{"class":5249,"line":5454},[5247,15800,9223],{"class":5825},[5247,15802,15803],{"class":6204},"'Test Loss Comparison'",[5247,15805,5948],{"class":5825},[5247,15807,6653],{"class":5870},[5247,15809,6055],{"class":5825},[5247,15811,6565],{"class":5885},[5247,15813,5948],{"class":5825},[5247,15815,6721],{"class":5870},[5247,15817,6055],{"class":5825},[5247,15819,6726],{"class":6204},[5247,15821,5924],{"class":5825},[5247,15823,15824,15826,15828,15830,15832],{"class":5249,"line":5460},[5247,15825,9262],{"class":5825},[5247,15827,6653],{"class":5870},[5247,15829,6055],{"class":5825},[5247,15831,6555],{"class":5885},[5247,15833,5924],{"class":5825},[5247,15835,15836,15838,15840,15842,15844],{"class":5249,"line":5466},[5247,15837,9249],{"class":5825},[5247,15839,6317],{"class":5870},[5247,15841,6055],{"class":5825},[5247,15843,6322],{"class":5885},[5247,15845,5924],{"class":5825},[5247,15847,15848],{"class":5249,"line":5472},[5247,15849,5278],{"emptyLinePlaceholder":5277},[5247,15851,15852],{"class":5249,"line":5477},[5247,15853,15854],{"class":5853},"# Графік 3: Learning Rate\n",[5247,15856,15857,15859,15861,15863,15865],{"class":5249,"line":5482},[5247,15858,9150],{"class":5825},[5247,15860,5808],{"class":5885},[5247,15862,5948],{"class":5825},[5247,15864,6216],{"class":5885},[5247,15866,6272],{"class":5825},[5247,15868,15869,15871,15873,15875],{"class":5249,"line":5488},[5247,15870,6281],{"class":5821},[5247,15872,15578],{"class":5825},[5247,15874,5984],{"class":5821},[5247,15876,15583],{"class":5825},[5247,15878,15879,15881,15883,15885,15887,15889,15891,15893,15895,15897,15899,15901,15903,15905,15907],{"class":5249,"line":5493},[5247,15880,15588],{"class":5825},[5247,15882,7619],{"class":6204},[5247,15884,6488],{"class":5825},[5247,15886,6327],{"class":5870},[5247,15888,15597],{"class":5825},[5247,15890,6418],{"class":5870},[5247,15892,15602],{"class":5825},[5247,15894,6307],{"class":5870},[5247,15896,6055],{"class":5825},[5247,15898,6264],{"class":5885},[5247,15900,5948],{"class":5825},[5247,15902,6317],{"class":5870},[5247,15904,6055],{"class":5825},[5247,15906,6450],{"class":5885},[5247,15908,5924],{"class":5825},[5247,15910,15911,15913,15915,15917,15919,15921,15923],{"class":5249,"line":5499},[5247,15912,9189],{"class":5825},[5247,15914,7712],{"class":6204},[5247,15916,5948],{"class":5825},[5247,15918,6653],{"class":5870},[5247,15920,6055],{"class":5825},[5247,15922,6500],{"class":5885},[5247,15924,5924],{"class":5825},[5247,15926,15927,15929,15931,15933,15935,15937,15939],{"class":5249,"line":5505},[5247,15928,9206],{"class":5825},[5247,15930,7730],{"class":6204},[5247,15932,5948],{"class":5825},[5247,15934,6653],{"class":5870},[5247,15936,6055],{"class":5825},[5247,15938,6500],{"class":5885},[5247,15940,5924],{"class":5825},[5247,15942,15943,15945,15948,15950,15952,15954,15956,15958,15960,15962,15964],{"class":5249,"line":5510},[5247,15944,9223],{"class":5825},[5247,15946,15947],{"class":6204},"'Learning Rate Schedule'",[5247,15949,5948],{"class":5825},[5247,15951,6653],{"class":5870},[5247,15953,6055],{"class":5825},[5247,15955,6565],{"class":5885},[5247,15957,5948],{"class":5825},[5247,15959,6721],{"class":5870},[5247,15961,6055],{"class":5825},[5247,15963,6726],{"class":6204},[5247,15965,5924],{"class":5825},[5247,15967,15968,15970,15972],{"class":5249,"line":5516},[5247,15969,9469],{"class":5825},[5247,15971,7774],{"class":6204},[5247,15973,5924],{"class":5825},[5247,15975,15976,15978,15980,15982,15984],{"class":5249,"line":5522},[5247,15977,9262],{"class":5825},[5247,15979,6653],{"class":5870},[5247,15981,6055],{"class":5825},[5247,15983,6555],{"class":5885},[5247,15985,5924],{"class":5825},[5247,15987,15988,15990,15992,15994,15996],{"class":5249,"line":5528},[5247,15989,9249],{"class":5825},[5247,15991,6317],{"class":5870},[5247,15993,6055],{"class":5825},[5247,15995,6322],{"class":5885},[5247,15997,5924],{"class":5825},[5247,15999,16000],{"class":5249,"line":5534},[5247,16001,5278],{"emptyLinePlaceholder":5277},[5247,16003,16004],{"class":5249,"line":5539},[5247,16005,16006],{"class":5853},"# Графік 4: Фінальна таблиця результатів\n",[5247,16008,16009,16011,16013,16015,16017],{"class":5249,"line":6401},[5247,16010,9150],{"class":5825},[5247,16012,5808],{"class":5885},[5247,16014,5948],{"class":5825},[5247,16016,5808],{"class":5885},[5247,16018,6272],{"class":5825},[5247,16020,16021,16024,16027],{"class":5249,"line":6407},[5247,16022,16023],{"class":5825},"ax.axis(",[5247,16025,16026],{"class":6204},"'off'",[5247,16028,5924],{"class":5825},[5247,16030,16031],{"class":5249,"line":6434},[5247,16032,5278],{"emptyLinePlaceholder":5277},[5247,16034,16035],{"class":5249,"line":6464},[5247,16036,16037],{"class":5825},"final_results = []\n",[5247,16039,16040,16042,16044,16046],{"class":5249,"line":6469},[5247,16041,6281],{"class":5821},[5247,16043,15578],{"class":5825},[5247,16045,5984],{"class":5821},[5247,16047,15583],{"class":5825},[5247,16049,16050,16053,16055,16057,16059],{"class":5249,"line":6475},[5247,16051,16052],{"class":5825},"    final_acc = hist[",[5247,16054,13846],{"class":6204},[5247,16056,14465],{"class":5825},[5247,16058,5808],{"class":5885},[5247,16060,6272],{"class":5825},[5247,16062,16063,16065,16068,16071,16073],{"class":5249,"line":6523},[5247,16064,13912],{"class":5825},[5247,16066,16067],{"class":5863},"max",[5247,16069,16070],{"class":5825},"(hist[",[5247,16072,13846],{"class":6204},[5247,16074,6267],{"class":5825},[5247,16076,16077,16080,16082,16085],{"class":5249,"line":6528},[5247,16078,16079],{"class":5825},"    best_epoch = hist[",[5247,16081,13846],{"class":6204},[5247,16083,16084],{"class":5825},"].index(best_acc) + ",[5247,16086,11072],{"class":5885},[5247,16088,16089,16092,16094,16096,16098,16101,16103,16106,16108,16110,16112,16114,16116,16118,16120],{"class":5249,"line":6534},[5247,16090,16091],{"class":5825},"    final_results.append([name, ",[5247,16093,6601],{"class":5859},[5247,16095,6817],{"class":6204},[5247,16097,6607],{"class":5859},[5247,16099,16100],{"class":5825},"final_acc",[5247,16102,14424],{"class":5859},[5247,16104,16105],{"class":6204},"%\"",[5247,16107,5948],{"class":5825},[5247,16109,6601],{"class":5859},[5247,16111,6817],{"class":6204},[5247,16113,6607],{"class":5859},[5247,16115,14531],{"class":5825},[5247,16117,14424],{"class":5859},[5247,16119,16105],{"class":6204},[5247,16121,16122],{"class":5825},", best_epoch])\n",[5247,16124,16125],{"class":5249,"line":6581},[5247,16126,5278],{"emptyLinePlaceholder":5277},[5247,16128,16129,16132,16135,16137,16140,16142,16145,16147,16150],{"class":5249,"line":6595},[5247,16130,16131],{"class":5825},"table_data = [[",[5247,16133,16134],{"class":6204},"'Scheduler'",[5247,16136,5948],{"class":5825},[5247,16138,16139],{"class":6204},"'Final Acc'",[5247,16141,5948],{"class":5825},[5247,16143,16144],{"class":6204},"'Best Acc'",[5247,16146,5948],{"class":5825},[5247,16148,16149],{"class":6204},"'Best Epoch'",[5247,16151,16152],{"class":5825},"]] + final_results\n",[5247,16154,16155,16158,16161,16164,16167,16169,16171,16173,16176,16178,16180],{"class":5249,"line":6626},[5247,16156,16157],{"class":5825},"table = ax.table(",[5247,16159,16160],{"class":5870},"cellText",[5247,16162,16163],{"class":5825},"=table_data, ",[5247,16165,16166],{"class":5870},"cellLoc",[5247,16168,6055],{"class":5825},[5247,16170,8297],{"class":6204},[5247,16172,5948],{"class":5825},[5247,16174,16175],{"class":5870},"loc",[5247,16177,6055],{"class":5825},[5247,16179,8297],{"class":6204},[5247,16181,12224],{"class":5825},[5247,16183,16184,16187,16189,16192,16194,16196,16198,16200,16202,16204],{"class":5249,"line":6663},[5247,16185,16186],{"class":5870},"                colWidths",[5247,16188,8065],{"class":5825},[5247,16190,16191],{"class":5885},"0.35",[5247,16193,5948],{"class":5825},[5247,16195,11326],{"class":5885},[5247,16197,5948],{"class":5825},[5247,16199,11326],{"class":5885},[5247,16201,5948],{"class":5825},[5247,16203,11326],{"class":5885},[5247,16205,6267],{"class":5825},[5247,16207,16208,16211,16213],{"class":5249,"line":6668},[5247,16209,16210],{"class":5825},"table.auto_set_font_size(",[5247,16212,9708],{"class":5859},[5247,16214,5924],{"class":5825},[5247,16216,16217,16220,16222],{"class":5249,"line":6687},[5247,16218,16219],{"class":5825},"table.set_fontsize(",[5247,16221,6555],{"class":5885},[5247,16223,5924],{"class":5825},[5247,16225,16226,16229,16231,16233,16235],{"class":5249,"line":6706},[5247,16227,16228],{"class":5825},"table.scale(",[5247,16230,5808],{"class":5885},[5247,16232,5948],{"class":5825},[5247,16234,6264],{"class":5885},[5247,16236,5924],{"class":5825},[5247,16238,16239],{"class":5249,"line":6731},[5247,16240,5278],{"emptyLinePlaceholder":5277},[5247,16242,16243],{"class":5249,"line":6745},[5247,16244,16245],{"class":5853},"# Колір заголовка\n",[5247,16247,16248,16250,16252,16254,16256,16258,16260],{"class":5249,"line":6759},[5247,16249,6281],{"class":5821},[5247,16251,6539],{"class":5825},[5247,16253,5984],{"class":5821},[5247,16255,5987],{"class":5863},[5247,16257,5867],{"class":5825},[5247,16259,6518],{"class":5885},[5247,16261,5874],{"class":5825},[5247,16263,16264,16267,16269,16272,16275],{"class":5249,"line":6774},[5247,16265,16266],{"class":5825},"    table[(",[5247,16268,6216],{"class":5885},[5247,16270,16271],{"class":5825},", i)].set_facecolor(",[5247,16273,16274],{"class":6204},"'#e2e8f0'",[5247,16276,5924],{"class":5825},[5247,16278,16279,16281,16283,16286,16289,16291,16293],{"class":5249,"line":6779},[5247,16280,16266],{"class":5825},[5247,16282,6216],{"class":5885},[5247,16284,16285],{"class":5825},", i)].set_text_props(",[5247,16287,16288],{"class":5870},"weight",[5247,16290,6055],{"class":5825},[5247,16292,6726],{"class":6204},[5247,16294,5924],{"class":5825},[5247,16296,16297],{"class":5249,"line":6785},[5247,16298,5278],{"emptyLinePlaceholder":5277},[5247,16300,16301],{"class":5249,"line":6791},[5247,16302,16303],{"class":5853},"# Виділимо найкращий результат\n",[5247,16305,16306,16309,16311,16314,16317,16319,16322,16325,16327,16329,16332,16334,16336,16338,16341,16343],{"class":5249,"line":6796},[5247,16307,16308],{"class":5825},"best_scheduler = ",[5247,16310,16067],{"class":5863},[5247,16312,16313],{"class":5825},"(results.items(), ",[5247,16315,16316],{"class":5870},"key",[5247,16318,6055],{"class":5825},[5247,16320,16321],{"class":5859},"lambda",[5247,16323,16324],{"class":5870}," x",[5247,16326,15502],{"class":5825},[5247,16328,16067],{"class":5863},[5247,16330,16331],{"class":5825},"(x[",[5247,16333,5808],{"class":5885},[5247,16335,7616],{"class":5825},[5247,16337,13846],{"class":6204},[5247,16339,16340],{"class":5825},"]))[",[5247,16342,6216],{"class":5885},[5247,16344,6272],{"class":5825},[5247,16346,16347,16349,16352,16354,16356,16359,16362,16364,16366],{"class":5249,"line":6802},[5247,16348,6281],{"class":5821},[5247,16350,16351],{"class":5825}," i, (name, _, _, _) ",[5247,16353,5984],{"class":5821},[5247,16355,6957],{"class":5863},[5247,16357,16358],{"class":5825},"(final_results, ",[5247,16360,16361],{"class":5870},"start",[5247,16363,6055],{"class":5825},[5247,16365,5808],{"class":5885},[5247,16367,5874],{"class":5825},[5247,16369,16370,16372],{"class":5249,"line":6822},[5247,16371,10248],{"class":5821},[5247,16373,16374],{"class":5825}," name == best_scheduler:\n",[5247,16376,16377,16379,16382,16384,16386,16388,16390],{"class":5249,"line":6876},[5247,16378,11038],{"class":5821},[5247,16380,16381],{"class":5825}," j ",[5247,16383,5984],{"class":5821},[5247,16385,5987],{"class":5863},[5247,16387,5867],{"class":5825},[5247,16389,6518],{"class":5885},[5247,16391,5874],{"class":5825},[5247,16393,16394,16397,16400],{"class":5249,"line":6894},[5247,16395,16396],{"class":5825},"            table[(i, j)].set_facecolor(",[5247,16398,16399],{"class":6204},"'#dcfce7'",[5247,16401,5924],{"class":5825},[5247,16403,16404],{"class":5249,"line":6899},[5247,16405,5278],{"emptyLinePlaceholder":5277},[5247,16407,16408],{"class":5249,"line":6911},[5247,16409,6782],{"class":5825},[5247,16411,16412,16415,16418,16420,16423,16425,16427,16429,16432,16434,16437],{"class":5249,"line":6921},[5247,16413,16414],{"class":5825},"plt.savefig(",[5247,16416,16417],{"class":6204},"'scheduler_comparison.png'",[5247,16419,5948],{"class":5825},[5247,16421,16422],{"class":5870},"dpi",[5247,16424,6055],{"class":5825},[5247,16426,12003],{"class":5885},[5247,16428,5948],{"class":5825},[5247,16430,16431],{"class":5870},"bbox_inches",[5247,16433,6055],{"class":5825},[5247,16435,16436],{"class":6204},"'tight'",[5247,16438,5924],{"class":5825},[5247,16440,16441],{"class":5249,"line":6927},[5247,16442,6788],{"class":5825},[5247,16444,16445],{"class":5249,"line":6932},[5247,16446,5278],{"emptyLinePlaceholder":5277},[5247,16448,16449],{"class":5249,"line":6938},[5247,16450,16451],{"class":5853},"# Детальна таблиця\n",[5247,16453,16454,16456,16458,16460,16462,16464,16467,16469,16472,16474],{"class":5249,"line":6947},[5247,16455,6805],{"class":5863},[5247,16457,5867],{"class":5825},[5247,16459,6817],{"class":6204},[5247,16461,6814],{"class":6813},[5247,16463,6817],{"class":6204},[5247,16465,16466],{"class":5825}," + ",[5247,16468,13891],{"class":6204},[5247,16470,16471],{"class":5825},"*",[5247,16473,7927],{"class":5885},[5247,16475,5924],{"class":5825},[5247,16477,16478,16480,16482,16485],{"class":5249,"line":6963},[5247,16479,6805],{"class":5863},[5247,16481,5867],{"class":5825},[5247,16483,16484],{"class":6204},"\"📊 ФІНАЛЬНІ РЕЗУЛЬТАТИ ЕКСПЕРИМЕНТУ\"",[5247,16486,5924],{"class":5825},[5247,16488,16489,16491,16493,16495,16497,16499],{"class":5249,"line":6984},[5247,16490,6805],{"class":5863},[5247,16492,5867],{"class":5825},[5247,16494,13891],{"class":6204},[5247,16496,16471],{"class":5825},[5247,16498,7927],{"class":5885},[5247,16500,5924],{"class":5825},[5247,16502,16503,16505,16507,16509,16511,16513,16515,16518,16520,16522,16525,16527,16529,16531,16533,16535,16537,16539,16542,16544,16546],{"class":5249,"line":6990},[5247,16504,6805],{"class":5863},[5247,16506,5867],{"class":5825},[5247,16508,6601],{"class":5859},[5247,16510,6817],{"class":6204},[5247,16512,6607],{"class":5859},[5247,16514,16134],{"class":6204},[5247,16516,16517],{"class":5859},":\u003C25}",[5247,16519,6841],{"class":5859},[5247,16521,16139],{"class":6204},[5247,16523,16524],{"class":5859},":\u003C12}",[5247,16526,6841],{"class":5859},[5247,16528,16144],{"class":6204},[5247,16530,16524],{"class":5859},[5247,16532,6841],{"class":5859},[5247,16534,16149],{"class":6204},[5247,16536,16524],{"class":5859},[5247,16538,6841],{"class":5859},[5247,16540,16541],{"class":6204},"'Покращення'",[5247,16543,6855],{"class":5859},[5247,16545,6817],{"class":6204},[5247,16547,5924],{"class":5825},[5247,16549,16550,16552,16554,16556,16558,16560],{"class":5249,"line":6996},[5247,16551,6805],{"class":5863},[5247,16553,5867],{"class":5825},[5247,16555,6883],{"class":6204},[5247,16557,16471],{"class":5825},[5247,16559,7927],{"class":5885},[5247,16561,5924],{"class":5825},[5247,16563,16564],{"class":5249,"line":7001},[5247,16565,5278],{"emptyLinePlaceholder":5277},[5247,16567,16568,16571,16573,16575,16577],{"class":5249,"line":7022},[5247,16569,16570],{"class":5825},"baseline_acc = history_fixed[",[5247,16572,13846],{"class":6204},[5247,16574,14465],{"class":5825},[5247,16576,5808],{"class":5885},[5247,16578,6272],{"class":5825},[5247,16580,16581],{"class":5249,"line":7050},[5247,16582,5278],{"emptyLinePlaceholder":5277},[5247,16584,16585,16587,16589,16591],{"class":5249,"line":7055},[5247,16586,6281],{"class":5821},[5247,16588,15578],{"class":5825},[5247,16590,5984],{"class":5821},[5247,16592,15583],{"class":5825},[5247,16594,16595,16597,16599,16601,16603],{"class":5249,"line":14209},[5247,16596,16052],{"class":5825},[5247,16598,13846],{"class":6204},[5247,16600,14465],{"class":5825},[5247,16602,5808],{"class":5885},[5247,16604,6272],{"class":5825},[5247,16606,16607,16609,16611,16613,16615],{"class":5249,"line":14215},[5247,16608,13912],{"class":5825},[5247,16610,16067],{"class":5863},[5247,16612,16070],{"class":5825},[5247,16614,13846],{"class":6204},[5247,16616,6267],{"class":5825},[5247,16618,16619,16621,16623,16625],{"class":5249,"line":14226},[5247,16620,16079],{"class":5825},[5247,16622,13846],{"class":6204},[5247,16624,16084],{"class":5825},[5247,16626,11072],{"class":5885},[5247,16628,16629],{"class":5249,"line":14236},[5247,16630,16631],{"class":5825},"    improvement = final_acc - baseline_acc\n",[5247,16633,16634],{"class":5249,"line":14246},[5247,16635,5973],{"class":5825},[5247,16637,16638,16641,16644,16646,16649,16651],{"class":5249,"line":14256},[5247,16639,16640],{"class":5825},"    marker = ",[5247,16642,16643],{"class":6204},"\"🏆\"",[5247,16645,7010],{"class":5821},[5247,16647,16648],{"class":5825}," name == best_scheduler ",[5247,16650,7016],{"class":5821},[5247,16652,16653],{"class":6204}," \"\"\n",[5247,16655,16656,16658,16660,16662,16664,16666,16669,16671,16673,16675,16678,16681,16683,16685,16687,16689,16691,16694,16696,16699,16701,16704,16706,16709,16711,16714,16716,16718],{"class":5249,"line":14274},[5247,16657,7058],{"class":5863},[5247,16659,5867],{"class":5825},[5247,16661,6601],{"class":5859},[5247,16663,6817],{"class":6204},[5247,16665,6607],{"class":5859},[5247,16667,16668],{"class":5825},"name",[5247,16670,16517],{"class":5859},[5247,16672,6841],{"class":5859},[5247,16674,16100],{"class":5825},[5247,16676,16677],{"class":5859},":\u003C12.2f}",[5247,16679,16680],{"class":6204},"% ",[5247,16682,6607],{"class":5859},[5247,16684,14531],{"class":5825},[5247,16686,16677],{"class":5859},[5247,16688,16680],{"class":6204},[5247,16690,6607],{"class":5859},[5247,16692,16693],{"class":5825},"best_epoch",[5247,16695,16524],{"class":5859},[5247,16697,16698],{"class":6204}," +",[5247,16700,6607],{"class":5859},[5247,16702,16703],{"class":5825},"improvement",[5247,16705,14424],{"class":5859},[5247,16707,16708],{"class":6204},"%  ",[5247,16710,6607],{"class":5859},[5247,16712,16713],{"class":5825},"marker",[5247,16715,6613],{"class":5859},[5247,16717,6817],{"class":6204},[5247,16719,5924],{"class":5825},[5247,16721,16722],{"class":5249,"line":14279},[5247,16723,5278],{"emptyLinePlaceholder":5277},[5247,16725,16726,16728,16730,16732,16734,16736],{"class":5249,"line":14285},[5247,16727,6805],{"class":5863},[5247,16729,5867],{"class":5825},[5247,16731,13891],{"class":6204},[5247,16733,16471],{"class":5825},[5247,16735,7927],{"class":5885},[5247,16737,5924],{"class":5825},[7107,16739,16740,16747,16754],{"v-slot:output":5242},[5191,16741,16742],{},[7112,16743],{"alt":16744,"className":16745,"src":16746},"Порівняння schedulers: Warm-up + Cosine показує найкращий результат",[7116],"\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling\u002F10.png",[15340,16748,16750,16751],{"id":16749},"фінальні-результати-експерименту","================================================================================\n📊 ",[5195,16752,16753],{},"ФІНАЛЬНІ РЕЗУЛЬТАТИ ЕКСПЕРИМЕНТУ",[7125,16755,16756,16775],{},[7128,16757,16758],{},[7131,16759,16760,16763,16766,16769,16772],{},[7134,16761,16762],{"align":7136},"Scheduler",[7134,16764,16765],{"align":7136},"Final Acc",[7134,16767,16768],{"align":7136},"Best Acc",[7134,16770,16771],{"align":7136},"Best Epoch",[7134,16773,16774],{"align":7136},"Покращення",[7151,16776,16777,16791,16804,16817,16831,16845],{},[7131,16778,16779,16782,16784,16786,16788],{},[7156,16780,16781],{"align":7136},"Fixed LR",[7156,16783,15355],{"align":7136},[7156,16785,15355],{"align":7136},[7156,16787,9048],{"align":7136},[7156,16789,16790],{"align":7136},"+0.00% (baseline)",[7131,16792,16793,16795,16797,16799,16801],{},[7156,16794,13176],{"align":7136},[7156,16796,15364],{"align":7136},[7156,16798,15364],{"align":7136},[7156,16800,9048],{"align":7136},[7156,16802,16803],{"align":7136},"+7.80% ✅",[7131,16805,16806,16808,16810,16812,16814],{},[7156,16807,13181],{"align":7136},[7156,16809,15373],{"align":7136},[7156,16811,15373],{"align":7136},[7156,16813,9048],{"align":7136},[7156,16815,16816],{"align":7136},"+8.75% ✅✅",[7131,16818,16819,16821,16823,16825,16828],{},[7156,16820,13186],{"align":7136},[7156,16822,15382],{"align":7136},[7156,16824,15382],{"align":7136},[7156,16826,16827],{"align":7136},"98",[7156,16829,16830],{"align":7136},"+8.10% ✅",[7131,16832,16833,16836,16838,16840,16842],{},[7156,16834,16835],{"align":7136},"Warm-up + Cosine",[7156,16837,15391],{"align":7136},[7156,16839,15391],{"align":7136},[7156,16841,8880],{"align":7136},[7156,16843,16844],{"align":7136},"+9.10% 🏆",[7131,16846,16847,16850,16852,16854,16856],{},[7156,16848,16849],{"align":7136},"================================================================================",[7156,16851],{"align":7136},[7156,16853],{"align":7136},[7156,16855],{"align":7136},[7156,16857],{"align":7136},[5544,16859,16861],{"id":16860},"інтерпретація-результатів","Інтерпретація результатів",[16863,16864,16865,16902,16936],"accordion",{},[16866,16867,16870],"accordion-item",{"icon":16868,"label":16869},"i-lucide-bar-chart","📊 Основні висновки",[9564,16871,16872,16878,16884,16890,16896],{},[5628,16873,16874,16877],{},[5195,16875,16876],{},"Fixed LR катастрофічно неефективний:"," 84.35% — на 9% гірше за будь-який scheduler. Модель застряє у субоптимальному мінімумі, бо LR занадто великий для fine-tuning.",[5628,16879,16880,16883],{},[5195,16881,16882],{},"StepLR — надійний baseline:"," +7.8% покращення. Прості різкі зменшення працюють, але не ідеально.",[5628,16885,16886,16889],{},[5195,16887,16888],{},"CosineAnnealingLR краще за StepLR:"," +8.75%. Плавне зменшення дозволяє кращу конвергенцію.",[5628,16891,16892,16895],{},[5195,16893,16894],{},"ReduceLROnPlateau адаптивний, але консервативний:"," +8.1%. Чекає 10 епох plateau перед зменшенням, що може бути занадто пізно.",[5628,16897,16898,16901],{},[5195,16899,16900],{},"Warm-up + Cosine — переможець:"," +9.1%. Обережний старт з warm-up запобігає ранній нестабільності, cosine забезпечує оптимальне зменшення.",[16866,16903,16905,16908,16919,16922,16933],{"icon":5214,"label":16904},"❓ Чому Warm-up допоміг?",[5191,16906,16907],{},"На початку навчання ваги випадкові (навіть після He initialization). Великий LR (0.1) може спричинити:",[5625,16909,16910,16913,16916],{},[5628,16911,16912],{},"Нестабільні градієнти у глибоких шарах",[5628,16914,16915],{},"\"Шокування\" BatchNorm статистики",[5628,16917,16918],{},"Ризик divergence у перші кілька епох",[5191,16920,16921],{},"Warm-up (5 епох від 1e-5 до 0.1) дозволяє моделі \"розігрітися\":",[5625,16923,16924,16927,16930],{},[5628,16925,16926],{},"Ваги стабілізуються",[5628,16928,16929],{},"BatchNorm накопичує коректні running statistics",[5628,16931,16932],{},"Градієнти стають передбачуваними",[5191,16934,16935],{},"Після цього cosine annealing забезпечує оптимальне зменшення LR.",[16866,16937,16939,16946,16967],{"icon":5214,"label":16938},"❓ Чому ReduceLROnPlateau не виграв?",[5191,16940,16941,16942,16945],{},"Хоча ReduceLROnPlateau ",[5195,16943,16944],{},"адаптивний"," і не потребує заздалегідь знати епохи для зменшення, він має два недоліки:",[9564,16947,16948,16961],{},[5628,16949,16950,5198,16953,16956,16957,16960],{},[5195,16951,16952],{},"Консерватизм:",[5244,16954,16955],{},"patience=10"," означає, що scheduler чекає 10 епох ",[5195,16958,16959],{},"після"," зупинки прогресу. За цей час модель марнує час, рухаючись занадто великими кроками біля мінімуму.",[5628,16962,16963,16966],{},[5195,16964,16965],{},"Шум у val_loss:"," Validation loss природно шумна (особливо для малих val sets). Scheduler може \"пропустити\" справжній plateau або спрацювати на випадковому сплеску.",[5191,16968,16969,16971,16972,16975],{},[5195,16970,7311],{}," ReduceLROnPlateau добрий для ",[5195,16973,16974],{},"першого експерименту"," з новою задачею, коли ви не знаєте, коли модель зупиниться. Але для фінального тренування краще використовувати Cosine з warm-up.",[5712,16977],{},[5186,16979,16981],{"id":16980},"практичні-рекомендації-як-обрати-scheduler","Практичні рекомендації — як обрати scheduler",[5191,16983,16984],{},"Підсумуймо всі знання у практичний гід:",[5544,16986,16988],{"id":16987},"чек-лист-вибору-scheduler","Чек-лист вибору scheduler",[16990,16991,16992,16996,17002,17023,17027,17084,17088,17111,17115],"steps",{},[5544,16993,16995],{"id":16994},"крок-1-оцініть-свій-сценарій","Крок 1. Оцініть свій сценарій",[5191,16997,16998,17001],{},[5195,16999,17000],{},"Питання:"," Чи це перший експеримент чи фінальне тренування?",[5625,17003,17004,17013],{},[5628,17005,17006,17009,17010,17012],{},[5195,17007,17008],{},"Перший експеримент:"," Використовуйте ",[5244,17011,13186],{}," (адаптивний, безпечний)",[5628,17014,17015,17009,17018,17020,17021],{},[5195,17016,17017],{},"Фінальне тренування:",[5244,17019,13181],{}," або ",[5244,17022,16835],{},[5544,17024,17026],{"id":17025},"крок-2-врахуйте-тривалість-навчання","Крок 2. Врахуйте тривалість навчання",[7125,17028,17029,17039],{},[7128,17030,17031],{},[7131,17032,17033,17036],{},[7134,17034,17035],{"align":7136},"Епохи",[7134,17037,17038],{"align":7136},"Рекомендація",[7151,17040,17041,17056,17068],{},[7131,17042,17043,17048],{},[7156,17044,17045],{"align":7136},[5195,17046,17047],{},"\u003C50",[7156,17049,17050,17052,17053],{"align":7136},[5244,17051,13176],{}," з milestones=",[5247,17054,17055],{},"25, 40",[7131,17057,17058,17063],{},[7156,17059,17060],{"align":7136},[5195,17061,17062],{},"50-200",[7156,17064,17065,17067],{"align":7136},[5244,17066,13181],{}," (T_max=num_epochs)",[7131,17069,17070,17075],{},[7156,17071,17072],{"align":7136},[5195,17073,17074],{},">200",[7156,17076,17077,17080,17081],{"align":7136},[5244,17078,17079],{},"ExponentialLR"," (gamma=0.98) або ",[5244,17082,17083],{},"CosineAnnealingWarmRestarts",[5544,17085,17087],{"id":17086},"крок-3-розгляньте-розмір-batch","Крок 3. Розгляньте розмір batch",[5625,17089,17090,17096,17102],{},[5628,17091,17092,17095],{},[5195,17093,17094],{},"Малий batch (\u003C64):"," Градієнти шумні → використовуйте консервативніший scheduler (StepLR)",[5628,17097,17098,17101],{},[5195,17099,17100],{},"Великий batch (>256):"," Градієнти стабільні → використовуйте агресивніший (OneCycleLR)",[5628,17103,17104,5198,17107,17110],{},[5195,17105,17106],{},"Дуже великий batch (>1024):",[5195,17108,17109],{},"Обов'язковий warm-up"," (5-10 епох)",[5544,17112,17114],{"id":17113},"крок-4-специфіка-архітектури","Крок 4. Специфіка архітектури",[5625,17116,17117,17125,17135],{},[5628,17118,17119,5198,17122,17124],{},[5195,17120,17121],{},"ResNet, DenseNet, EfficientNet:",[5244,17123,13181],{}," (перевірений вибір)",[5628,17126,17127,5198,17130,17020,17133],{},[5195,17128,17129],{},"Transformers (BERT, GPT):",[5244,17131,17132],{},"Warm-up + Linear Decay",[5244,17134,16835],{},[5628,17136,17137,5198,17140,17142],{},[5195,17138,17139],{},"RNN, LSTM:",[5244,17141,13186],{}," (важко передбачити конвергенцію)",[5544,17144,17146],{"id":17145},"універсальний-рецепт-для-cnn","Універсальний рецепт для CNN",[5191,17148,17149],{},"Якщо сумніваєтесь, використовуйте цю конфігурацію — вона працює для 90% задач:",[5237,17151,17153],{"className":5812,"code":17152,"language":5814,"meta":5242,"style":5242},"import torch.optim as optim\n\n# Optimizer\noptimizer = optim.SGD(\n    model.parameters(),\n    lr=0.1,           # Початковий LR\n    momentum=0.9,\n    weight_decay=5e-4,\n    nesterov=True     # Nesterov momentum трохи краще\n)\n\n# Scheduler: Warm-up (5 епох) + CosineAnnealing\nscheduler = WarmupCosineScheduler(\n    optimizer,\n    warmup_epochs=5,\n    total_epochs=100,\n    eta_min=1e-6,\n    warmup_start_lr=1e-5\n)\n\n# У тренувальному циклі\nfor epoch in range(num_epochs):\n    train_one_epoch(...)\n    validate(...)\n    scheduler.step()  # Оновлення LR\n",[5244,17154,17155,17165,17169,17174,17179,17184,17198,17209,17220,17232,17236,17240,17245,17250,17254,17265,17276,17286,17296,17300,17304,17309,17322,17327,17332],{"__ignoreMap":5242},[5247,17156,17157,17159,17161,17163],{"class":5249,"line":5250},[5247,17158,5822],{"class":5821},[5247,17160,7473],{"class":5825},[5247,17162,5829],{"class":5821},[5247,17164,7478],{"class":5825},[5247,17166,17167],{"class":5249,"line":5256},[5247,17168,5278],{"emptyLinePlaceholder":5277},[5247,17170,17171],{"class":5249,"line":5262},[5247,17172,17173],{"class":5853},"# Optimizer\n",[5247,17175,17176],{"class":5249,"line":5268},[5247,17177,17178],{"class":5825},"optimizer = optim.SGD(\n",[5247,17180,17181],{"class":5249,"line":5274},[5247,17182,17183],{"class":5825},"    model.parameters(),\n",[5247,17185,17186,17189,17191,17193,17195],{"class":5249,"line":5281},[5247,17187,17188],{"class":5870},"    lr",[5247,17190,6055],{"class":5825},[5247,17192,6058],{"class":5885},[5247,17194,12615],{"class":5825},[5247,17196,17197],{"class":5853},"# Початковий LR\n",[5247,17199,17200,17203,17205,17207],{"class":5249,"line":5287},[5247,17201,17202],{"class":5870},"    momentum",[5247,17204,6055],{"class":5825},[5247,17206,7531],{"class":5885},[5247,17208,12224],{"class":5825},[5247,17210,17211,17214,17216,17218],{"class":5249,"line":5293},[5247,17212,17213],{"class":5870},"    weight_decay",[5247,17215,6055],{"class":5825},[5247,17217,13816],{"class":5885},[5247,17219,12224],{"class":5825},[5247,17221,17222,17225,17227,17229],{"class":5249,"line":5299},[5247,17223,17224],{"class":5870},"    nesterov",[5247,17226,6055],{"class":5825},[5247,17228,9984],{"class":5859},[5247,17230,17231],{"class":5853},"     # Nesterov momentum трохи краще\n",[5247,17233,17234],{"class":5249,"line":5304},[5247,17235,5924],{"class":5825},[5247,17237,17238],{"class":5249,"line":5310},[5247,17239,5278],{"emptyLinePlaceholder":5277},[5247,17241,17242],{"class":5249,"line":5316},[5247,17243,17244],{"class":5853},"# Scheduler: Warm-up (5 епох) + CosineAnnealing\n",[5247,17246,17247],{"class":5249,"line":5322},[5247,17248,17249],{"class":5825},"scheduler = WarmupCosineScheduler(\n",[5247,17251,17252],{"class":5249,"line":5328},[5247,17253,9653],{"class":5825},[5247,17255,17256,17259,17261,17263],{"class":5249,"line":5334},[5247,17257,17258],{"class":5870},"    warmup_epochs",[5247,17260,6055],{"class":5825},[5247,17262,6147],{"class":5885},[5247,17264,12224],{"class":5825},[5247,17266,17267,17270,17272,17274],{"class":5249,"line":5340},[5247,17268,17269],{"class":5870},"    total_epochs",[5247,17271,6055],{"class":5825},[5247,17273,9048],{"class":5885},[5247,17275,12224],{"class":5825},[5247,17277,17278,17280,17282,17284],{"class":5249,"line":5346},[5247,17279,11970],{"class":5870},[5247,17281,6055],{"class":5825},[5247,17283,9058],{"class":5885},[5247,17285,12224],{"class":5825},[5247,17287,17288,17291,17293],{"class":5249,"line":5352},[5247,17289,17290],{"class":5870},"    warmup_start_lr",[5247,17292,6055],{"class":5825},[5247,17294,17295],{"class":5885},"1e-5\n",[5247,17297,17298],{"class":5249,"line":5358},[5247,17299,5924],{"class":5825},[5247,17301,17302],{"class":5249,"line":5364},[5247,17303,5278],{"emptyLinePlaceholder":5277},[5247,17305,17306],{"class":5249,"line":5369},[5247,17307,17308],{"class":5853},"# У тренувальному циклі\n",[5247,17310,17311,17313,17315,17317,17319],{"class":5249,"line":5375},[5247,17312,6281],{"class":5821},[5247,17314,7599],{"class":5825},[5247,17316,5984],{"class":5821},[5247,17318,5987],{"class":5863},[5247,17320,17321],{"class":5825},"(num_epochs):\n",[5247,17323,17324],{"class":5249,"line":5380},[5247,17325,17326],{"class":5825},"    train_one_epoch(...)\n",[5247,17328,17329],{"class":5249,"line":5386},[5247,17330,17331],{"class":5825},"    validate(...)\n",[5247,17333,17334,17337],{"class":5249,"line":5392},[5247,17335,17336],{"class":5825},"    scheduler.step()  ",[5247,17338,17339],{"class":5853},"# Оновлення LR\n",[5544,17341,17343],{"id":17342},"коли-не-використовувати-scheduling","Коли НЕ використовувати scheduling",[5191,17345,17346],{},"У деяких випадках фіксований LR насправді краще:",[5209,17348,17349,17365,17369],{},[5212,17350,17352,17359],{"icon":2865,"title":17351},"🔬 Transfer Learning з малим датасетом",[5191,17353,17354,17355,17358],{},"Якщо fine-tune pretrained модель на малому датасеті (\u003C1000 зображень), використовуйте ",[5195,17356,17357],{},"малий фіксований LR"," (1e-4 або 1e-5).",[5191,17360,17361,17364],{},[5195,17362,17363],{},"Чому:"," Pretrained ваги вже близькі до оптимуму, великий LR або aggressive scheduling можуть зруйнувати їх.",[5212,17366,17368],{"icon":92,"title":17367},"⚡ Few-shot learning","У few-shot сценаріях (5-10 прикладів на клас) навчання триває 10-20 епох. Scheduling не встигає \"розігрітися\".",[5212,17370,17372],{"icon":13234,"title":17371},"🎯 Hyperparameter tuning","Коли шукаєте оптимальні hyperparameters (learning rate, weight decay, архітектура), спочатку використовуйте фіксований LR для швидких експериментів.",[5712,17374],{},[5186,17376,17378],{"id":17377},"підсумки","Підсумки",[5209,17380,17381,17415],{},[5212,17382,17385],{"icon":17383,"title":17384},"i-lucide-lightbulb","🎯 Ключові інсайти",[9564,17386,17387,17393,17398,17404,17409],{},[5628,17388,17389,17392],{},[5195,17390,17391],{},"Фіксований LR неефективний"," для більшості задач глибокого навчання",[5628,17394,17395,17397],{},[5195,17396,13181],{}," — найкращий універсальний вибір для CNN",[5628,17399,17400,17403],{},[5195,17401,17402],{},"Warm-up критичний"," для великих batch sizes (>256) та дуже глибоких мереж",[5628,17405,17406,17408],{},[5195,17407,13186],{}," добрий для першого експерименту, але не оптимальний для фінального",[5628,17410,17411,17414],{},[5195,17412,17413],{},"OneCycleLR"," — найшвидша конвергенція, але потребує ретельного налаштування",[5212,17416,17418,17421,17440],{"icon":16868,"title":17417},"📊 Емпіричні результати",[5191,17419,17420],{},"На нашому експерименті (ResNet-18 на CIFAR-10):",[5625,17422,17423,17426,17429,17432,17435],{},[5628,17424,17425],{},"Fixed LR: 84.35% ❌",[5628,17427,17428],{},"StepLR: 92.15% ✅",[5628,17430,17431],{},"CosineAnnealing: 93.10% ✅✅",[5628,17433,17434],{},"ReduceLROnPlateau: 92.45% ✅",[5628,17436,17437,15392],{},[5195,17438,17439],{},"Warm-up + Cosine: 93.45%",[5191,17441,17442,17445],{},[5195,17443,17444],{},"Покращення:"," +9.1% порівняно з baseline!",[7211,17447,17448,17453,17460,17482],{},[5191,17449,17450],{},[5195,17451,17452],{},"Наступний крок:",[5191,17454,17455,17456,17459],{},"У фінальній статті цього модуля ми об'єднаємо ",[5195,17457,17458],{},"всі техніки",", вивчені у попередніх розділах:",[5625,17461,17462,17465,17468,17471,17474,17477],{},[5628,17463,17464],{},"Mini-batch Gradient Descent",[5628,17466,17467],{},"He Weight Initialization",[5628,17469,17470],{},"Batch Normalization",[5628,17472,17473],{},"Dropout",[5628,17475,17476],{},"ResNet архітектура",[5628,17478,17479],{},[5195,17480,17481],{},"Learning Rate Scheduling (ця стаття)",[5191,17483,17484,17485,17488],{},"...щоб побудувати ",[5195,17486,17487],{},"production-ready"," глибокий класифікатор із state-of-the-art якістю!",[17490,17491,17492],"style",{},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html 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.sN1BT{--shiki-light:#267F99;--shiki-default:#4EC9B0;--shiki-dark:#4EC9B0}",{"title":5242,"searchDepth":5256,"depth":5256,"links":17494},[17495,17498,17503,17510,17515,17521,17530],{"id":5188,"depth":5256,"text":5189,"children":17496},[17497],{"id":5546,"depth":5262,"text":5547},{"id":5716,"depth":5256,"text":5717,"children":17499},[17500,17501,17502],{"id":5723,"depth":5262,"text":5724},{"id":5777,"depth":5262,"text":5778},{"id":7256,"depth":5262,"text":7257},{"id":7321,"depth":5256,"text":7322,"children":17504},[17505,17506,17507,17508,17509],{"id":7332,"depth":5262,"text":7333},{"id":8006,"depth":5262,"text":8007},{"id":8478,"depth":5262,"text":8479},{"id":8958,"depth":5262,"text":8959},{"id":9585,"depth":5262,"text":9586},{"id":10499,"depth":5256,"text":10500,"children":17511},[17512,17513,17514],{"id":10513,"depth":5262,"text":10514},{"id":11849,"depth":5262,"text":11850},{"id":12507,"depth":5262,"text":12508},{"id":13159,"depth":5256,"text":13160,"children":17516},[17517,17518,17519,17520],{"id":13194,"depth":5262,"text":13195},{"id":13252,"depth":5262,"text":13253},{"id":15395,"depth":5262,"text":15396},{"id":16860,"depth":5262,"text":16861},{"id":16980,"depth":5256,"text":16981,"children":17522},[17523,17524,17525,17526,17527,17528,17529],{"id":16987,"depth":5262,"text":16988},{"id":16994,"depth":5262,"text":16995},{"id":17025,"depth":5262,"text":17026},{"id":17086,"depth":5262,"text":17087},{"id":17113,"depth":5262,"text":17114},{"id":17145,"depth":5262,"text":17146},{"id":17342,"depth":5262,"text":17343},{"id":17377,"depth":5256,"text":17378},"Проблема фіксованого learning rate, типи schedulers (Step, Exponential, Cosine, ReduceLROnPlateau), warm-up та warm restarts, практична реалізація та експериментальне порівняння.","md",null,{},{"title":3976,"description":17531},"gQSvOYDcBkwHK9Dd0JApoU-kLKQtxxK6pf4iezxb_iU",[17538,17540],{"title":3972,"path":3973,"stem":3974,"description":17539,"children":-1},"Проблема degradation у дуже глибоких мережах, ідея Skip Connections, реалізація Residual Blocks, побудова повноцінної ResNet-подібної архітектури, best practices та порівняльний експеримент.",{"title":3980,"path":3981,"stem":3982,"description":17541,"children":-1},"Комплексний проєкт на CIFAR-100 із застосуванням усіх вивчених технік. Від baseline до фінальної моделі через покрокові покращення, візуалізацію результатів та порівняльний аналіз.",1791986835584]