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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":3964,"body":5182,"description":13726,"extension":13727,"links":13728,"meta":13729,"navigation":5648,"path":3965,"seo":13730,"stem":3966,"__hash__":13731},"docs\u002F16.ai-python\u002F16.batching-normalization-deep-networks\u002F03.batch-normalization.md",{"type":5183,"value":5184,"toc":13694},"minimark",[5185,5190,5199,5202,5209,5230,5241,5303,5306,5310,5321,5326,5338,5350,5357,5432,5439,5443,5462,5531,7149,7184,7186,7190,7197,7201,7212,7217,7220,7223,7228,7231,7242,7259,7264,7267,7270,7297,7302,7316,7330,7333,7344,7506,7528,7530,7534,7537,7624,7643,7645,7649,7652,7656,7666,7796,7806,7810,7818,7867,7872,7880,7884,7953,7988,7990,7994,8005,8009,8020,8023,8026,8031,8035,8046,8049,8052,8058,8063,8094,8107,8633,8742,8744,8748,8751,8817,9741,9745,9839,9879,9881,9885,9888,13071,13101,13103,13107,13110,13199,13203,13272,13319,13321,13325,13652,13682,13684,13690],[5186,5187,5189],"h2",{"id":5188},"революція-2015-року-техніка-що-змінила-глибоке-навчання","Революція 2015 року — техніка, що змінила глибоке навчання",[5191,5192,5193,5194,5198],"p",{},"У попередній статті ми опанували техніки правильної ініціалізації ваг: Xavier для tanh\u002Fsigmoid та He для ReLU. Ці методи забезпечують хороший старт навчання, зберігаючи дисперсію активацій стабільною на початку. Але що відбувається ",[5195,5196,5197],"strong",{},"під час навчання",", коли ваги починають змінюватися?",[5191,5200,5201],{},"Уявіть ситуацію: ви навчаєте 20-шарову мережу. Перші кілька епох все йде добре — loss зменшується, accuracy зростає. Але потім прогрес різко сповільнюється. Learning rate доводиться зменшувати до 0.001, інакше модель нестабільна. Навчання, яке мало зайняти кілька годин, розтягується на дні. Знайоме відчуття?",[5191,5203,5204,5205,5208],{},"У 2015 році Sergey Ioffe та Christian Szegedy з Google опублікували статтю ",[5195,5206,5207],{},"«Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift»",", яка назавжди змінила ландшафт глибокого навчання. Їхня техніка дозволила:",[5210,5211,5212,5217,5221,5226],"card-group",{},[5213,5214,5216],"card",{"icon":92,"title":5215},"⚡ Прискорити навчання у 5-10 разів","Learning rate можна збільшити з 0.001 до 0.1 без втрати стабільності. Епоха, яка займала 10 хвилин, тепер займає 2 хвилини для досягнення тієї ж точності.",[5213,5218,5220],{"icon":943,"title":5219},"🏗️ Навчати дуже глибокі мережі","До Batch Normalization мережі глибше 20 шарів були важко навчуваними. З BN стали можливими ResNet (152 шари), Inception (22 шари), VGG (19 шарів). Сьогодні мережі з 100+ шарами — стандарт індустрії.",[5213,5222,5225],{"icon":5223,"title":5224},"i-lucide-target","🎯 Покращити фінальну точність","На ImageNet класифікації Batch Normalization покращила top-5 accuracy з 89.2% до 92.7% при тій самій архітектурі. Для деяких задач — приріст до 5%.",[5213,5227,5229],{"icon":4660,"title":5228},"🛡️ Зменшити перенавчання","Batch Normalization діє як імпліцитна регуляризація, зменшуючи потребу в Dropout та агресивній data augmentation.",[5191,5231,5232,5233,5236,5237,5240],{},"Сьогодні ",[5195,5234,5235],{},"практично кожна сучасна архітектура"," (ResNet, DenseNet, EfficientNet, Transformer) використовує Batch Normalization або його варіанти (Layer Normalization, Group Normalization). Це не просто «гарна практика» — це ",[5195,5238,5239],{},"необхідність"," для навчання глибоких мереж.",[5210,5242,5243,5268],{},[5213,5244,5246],{"icon":5223,"title":5245},"🎯 Мета статті",[5247,5248,5249,5253,5256,5259,5262,5265],"ul",{},[5250,5251,5252],"li",{},"Зрозуміти проблему Internal Covariate Shift та її вплив на навчання",[5250,5254,5255],{},"Опанувати математику Batch Normalization: нормалізацію, масштабування та зсув",[5250,5257,5258],{},"Дослідити, чому BN дозволяє використовувати великі learning rates",[5250,5260,5261],{},"Розібратися у критичній різниці між train та eval режимами",[5250,5263,5264],{},"Навчитися правильно розміщувати BN шари у архітектурі",[5250,5266,5267],{},"Провести експеримент на CIFAR-10: CNN з та без BN",[5213,5269,5271],{"icon":4618,"title":5270},"🔑 Ключові терміни",[5247,5272,5273,5279,5285,5291,5297],{},[5250,5274,5275,5278],{},[5195,5276,5277],{},"Internal Covariate Shift:"," зміна розподілу входів кожного шару під час навчання",[5250,5280,5281,5284],{},[5195,5282,5283],{},"Normalization:"," перетворення даних до стандартного розподілу з μ=0, σ²=1",[5250,5286,5287,5290],{},[5195,5288,5289],{},"Learnable Parameters γ, β:"," масштабування та зсув після нормалізації (навчаються градієнтним спуском)",[5250,5292,5293,5296],{},[5195,5294,5295],{},"Running Statistics:"," експоненціальне moving average μ та σ², що використовуються при inference",[5250,5298,5299,5302],{},[5195,5300,5301],{},"Train\u002FEval Mode:"," критична відмінність поведінки BN під час навчання та тестування",[5304,5305],"hr",{},[5186,5307,5309],{"id":5308},"проблема-internal-covariate-shift","Проблема: Internal Covariate Shift",[5191,5311,5312,5313,5316,5317,5320],{},"Перш ніж розглядати розв'язання, зрозуміймо проблему глибше. Що таке ",[5195,5314,5315],{},"covariate shift"," у статистиці, і чому він виникає ",[5195,5318,5319],{},"всередині"," нейронної мережі?",[5322,5323,5325],"h3",{"id":5324},"covariate-shift-у-машинному-навчанні","Covariate Shift у машинному навчанні",[5191,5327,5328,5329,5331,5332,5337],{},"У класичному машинному навчанні ",[5195,5330,5315],{}," означає, що розподіл вхідних даних ",[5333,5334],"math-formula",{"tex":5335,":inline":5336},"\\mathbf{x}","true"," змінюється між тренувальним та тестовим датасетами. Наприклад:",[5210,5339,5340,5345],{},[5213,5341,5344],{"icon":5342,"title":5343},"i-lucide-image","📸 Розпізнавання зображень","Модель навчена на денних фотографіях, але на продакшені отримує нічні знімки. Розподіл пікселів радикально інший — модель деградує.",[5213,5346,5349],{"icon":5347,"title":5348},"i-lucide-dollar-sign","💰 Кредитний скоринг","Модель навчена на даних до 2020 року, але пандемія COVID-19 змінила економічну поведінку людей. Розподіл доходів, витрат та кредитних історій зсунувся.",[5191,5351,5352,5353,5356],{},"Класичне розв'язання covariate shift — ",[5195,5354,5355],{},"нормалізація вхідних даних",". Ми завжди робимо це перед навчанням:",[5358,5359,5364],"pre",{"className":5360,"code":5361,"language":5362,"meta":5363,"style":5363},"language-python shiki shiki-themes light-plus dark-plus dark-plus","# Нормалізація зображень до [-1, 1] або стандартизація\ntransform = transforms.Normalize(mean=[0.485, 0.456, 0.406],\n                                std=[0.229, 0.224, 0.225])\n","python","",[5365,5366,5367,5376,5408],"code",{"__ignoreMap":5363},[5368,5369,5372],"span",{"class":5370,"line":5371},"line",1,[5368,5373,5375],{"class":5374},"spJ8K","# Нормалізація зображень до [-1, 1] або стандартизація\n",[5368,5377,5379,5383,5387,5390,5394,5397,5400,5402,5405],{"class":5370,"line":5378},2,[5368,5380,5382],{"class":5381},"sHH4Y","transform = transforms.Normalize(",[5368,5384,5386],{"class":5385},"siwwj","mean",[5368,5388,5389],{"class":5381},"=[",[5368,5391,5393],{"class":5392},"sJj4R","0.485",[5368,5395,5396],{"class":5381},", ",[5368,5398,5399],{"class":5392},"0.456",[5368,5401,5396],{"class":5381},[5368,5403,5404],{"class":5392},"0.406",[5368,5406,5407],{"class":5381},"],\n",[5368,5409,5411,5414,5416,5419,5421,5424,5426,5429],{"class":5370,"line":5410},3,[5368,5412,5413],{"class":5385},"                                std",[5368,5415,5389],{"class":5381},[5368,5417,5418],{"class":5392},"0.229",[5368,5420,5396],{"class":5381},[5368,5422,5423],{"class":5392},"0.224",[5368,5425,5396],{"class":5381},[5368,5427,5428],{"class":5392},"0.225",[5368,5430,5431],{"class":5381},"])\n",[5191,5433,5434,5435,5438],{},"Але що відбувається ",[5195,5436,5437],{},"всередині мережі",", після першого шару?",[5322,5440,5442],{"id":5441},"internal-covariate-shift-проблема-кожного-шару","Internal Covariate Shift — проблема кожного шару",[5191,5444,5445,5446,5449,5450,5453,5454,5457,5458,5461],{},"Розглянемо глибоку мережу. Нехай ",[5333,5447],{"tex":5448,":inline":5336},"\\mathbf{a}^{(l)}"," — активації ",[5333,5451],{"tex":5452,":inline":5336},"l","-го шару. Ці активації є ",[5195,5455,5456],{},"входами"," для шару ",[5333,5459],{"tex":5460,":inline":5336},"(l+1)",". Під час навчання відбувається наступне:",[5463,5464,5465,5469,5479,5483,5498,5502,5520,5524],"steps",{},[5322,5466,5468],{"id":5467},"крок-1-початок-епохи","Крок 1. Початок епохи",[5191,5470,5471,5472,5475,5476,5478],{},"Ваги ",[5333,5473],{"tex":5474,":inline":5336},"\\mathbf{W}^{(1)}, \\mathbf{W}^{(2)}, \\ldots, \\mathbf{W}^{(L)}"," мають певні значення (наприклад, після He ініціалізації). Розподіл активацій ",[5333,5477],{"tex":5448,":inline":5336}," стабільний.",[5322,5480,5482],{"id":5481},"крок-2-перша-міні-батч-ітерація","Крок 2. Перша міні-батч ітерація",[5191,5484,5485,5486,5489,5490,5493,5494,5497],{},"Обчислюємо градієнти та оновлюємо ваги ",[5195,5487,5488],{},"нижніх шарів"," ",[5333,5491],{"tex":5492,":inline":5336},"\\mathbf{W}^{(1)}, \\mathbf{W}^{(2)}",". Ці оновлення змінюють розподіл їхніх виходів ",[5333,5495],{"tex":5496,":inline":5336},"\\mathbf{a}^{(1)}, \\mathbf{a}^{(2)}",".",[5322,5499,5501],{"id":5500},"крок-3-наступна-ітерація","Крок 3. Наступна ітерація",[5191,5503,5504,5505,5508,5509,5489,5512,5515,5516,5519],{},"Шар ",[5333,5506],{"tex":5507,":inline":5336},"(3)"," тепер отримує ",[5195,5510,5511],{},"іншій розподіл входів",[5333,5513],{"tex":5514,":inline":5336},"\\mathbf{a}^{(2)}",", ніж у попередній ітерації. Його ваги ",[5333,5517],{"tex":5518,":inline":5336},"\\mathbf{W}^{(3)}"," були налаштовані на старий розподіл, а тепер бачать новий!",[5322,5521,5523],{"id":5522},"крок-4-накопичення-ефекту","Крок 4. Накопичення ефекту",[5191,5525,5526,5527,5530],{},"Кожен шар постійно адаптується до ",[5195,5528,5529],{},"рухомої мішені"," — розподілу входів, що змінюється через оновлення нижніх шарів. Чим глибша мережа, тим сильніший ефект.",[5532,5533,5536,5547,6556],"jupyter-notebook",{"title":5534,"kernel":5535},"internal_covariate_shift_demo.ipynb","Python 3.11 (ipykernel)",[5537,5538,5540,5544],"jupyter-cell",{"type":5539},"markdown",[5322,5541,5543],{"id":5542},"візуалізація-internal-covariate-shift","Візуалізація Internal Covariate Shift",[5191,5545,5546],{},"Побудуємо просту 5-шарову мережу та відстежимо, як змінюється розподіл активацій 3-го шару протягом перших 100 ітерацій навчання.",[5537,5548,5551,6477],{"execution-count":5549,"execution-time":5550},"1","3.2s",[5358,5552,5554],{"className":5360,"code":5553,"language":5362,"meta":5363,"style":5363},"import torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader\nfrom torchvision import datasets, transforms\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n# Проста мережа БЕЗ Batch Normalization\nclass SimpleNet(nn.Module):\n    def __init__(self):\n        super(SimpleNet, self).__init__()\n        self.fc1 = nn.Linear(784, 256)\n        self.fc2 = nn.Linear(256, 256)\n        self.fc3 = nn.Linear(256, 256)  # Будемо моніторити цей шар\n        self.fc4 = nn.Linear(256, 128)\n        self.fc5 = nn.Linear(128, 10)\n        self.relu = nn.ReLU()\n    \n    def forward(self, x, return_layer3=False):\n        x = x.view(x.size(0), -1)\n        x = self.relu(self.fc1(x))\n        x = self.relu(self.fc2(x))\n        layer3_input = x.clone()  # Зберегти вхід 3-го шару\n        x = self.relu(self.fc3(x))\n        x = self.relu(self.fc4(x))\n        x = self.fc5(x)\n        \n        if return_layer3:\n            return x, layer3_input\n        return x\n\n# Ініціалізація\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\nmodel = SimpleNet().to(device)\ncriterion = nn.CrossEntropyLoss()\noptimizer = optim.SGD(model.parameters(), lr=0.01, momentum=0.9)\n\n# MNIST DataLoader\ntransform = transforms.Compose([\n    transforms.ToTensor(),\n    transforms.Normalize((0.1307,), (0.3081,))\n])\ntrain_dataset = datasets.MNIST('.\u002Fdata', train=True, download=True, transform=transform)\ntrain_loader = DataLoader(train_dataset, batch_size=128, shuffle=True)\n\n# Збереження статистики розподілу входів 3-го шару\nlayer3_means = []\nlayer3_stds = []\n\nmodel.train()\nfor iteration, (images, labels) in enumerate(train_loader):\n    if iteration >= 100:  # Перші 100 ітерацій\n        break\n    \n    images, labels = images.to(device), labels.to(device)\n    \n    # Forward з збереженням активацій\n    outputs, layer3_input = model(images, return_layer3=True)\n    loss = criterion(outputs, labels)\n    \n    # Backward та оптимізація\n    optimizer.zero_grad()\n    loss.backward()\n    optimizer.step()\n    \n    # Статистика входу 3-го шару\n    with torch.no_grad():\n        mean = layer3_input.mean().item()\n        std = layer3_input.std().item()\n        layer3_means.append(mean)\n        layer3_stds.append(std)\n\nprint(f\"✅ Відстежено {len(layer3_means)} ітерацій навчання\")\nprint(f\"   Початкове середнє входу 3-го шару: {layer3_means[0]:.4f}\")\nprint(f\"   Фінальне середнє входу 3-го шару:  {layer3_means[-1]:.4f}\")\nprint(f\"   Зміна: {abs(layer3_means[-1] - layer3_means[0]):.4f}\")\n",[5365,5555,5556,5565,5578,5590,5604,5617,5630,5643,5650,5656,5681,5698,5718,5738,5754,5774,5791,5808,5816,5822,5852,5868,5884,5898,5907,5921,5935,5945,5951,5960,5969,5978,5983,5989,6013,6019,6025,6051,6056,6062,6068,6074,6092,6097,6133,6157,6162,6168,6174,6180,6185,6191,6209,6227,6233,6238,6244,6249,6255,6269,6275,6280,6286,6292,6298,6304,6309,6315,6324,6330,6336,6342,6348,6353,6384,6414,6441],{"__ignoreMap":5363},[5368,5557,5558,5562],{"class":5370,"line":5371},[5368,5559,5561],{"class":5560},"s8xlr","import",[5368,5563,5564],{"class":5381}," torch\n",[5368,5566,5567,5569,5572,5575],{"class":5370,"line":5378},[5368,5568,5561],{"class":5560},[5368,5570,5571],{"class":5381}," torch.nn ",[5368,5573,5574],{"class":5560},"as",[5368,5576,5577],{"class":5381}," nn\n",[5368,5579,5580,5582,5585,5587],{"class":5370,"line":5410},[5368,5581,5561],{"class":5560},[5368,5583,5584],{"class":5381}," torch.optim ",[5368,5586,5574],{"class":5560},[5368,5588,5589],{"class":5381}," optim\n",[5368,5591,5593,5596,5599,5601],{"class":5370,"line":5592},4,[5368,5594,5595],{"class":5560},"from",[5368,5597,5598],{"class":5381}," torch.utils.data ",[5368,5600,5561],{"class":5560},[5368,5602,5603],{"class":5381}," DataLoader\n",[5368,5605,5607,5609,5612,5614],{"class":5370,"line":5606},5,[5368,5608,5595],{"class":5560},[5368,5610,5611],{"class":5381}," torchvision ",[5368,5613,5561],{"class":5560},[5368,5615,5616],{"class":5381}," datasets, transforms\n",[5368,5618,5620,5622,5625,5627],{"class":5370,"line":5619},6,[5368,5621,5561],{"class":5560},[5368,5623,5624],{"class":5381}," matplotlib.pyplot ",[5368,5626,5574],{"class":5560},[5368,5628,5629],{"class":5381}," plt\n",[5368,5631,5633,5635,5638,5640],{"class":5370,"line":5632},7,[5368,5634,5561],{"class":5560},[5368,5636,5637],{"class":5381}," numpy ",[5368,5639,5574],{"class":5560},[5368,5641,5642],{"class":5381}," np\n",[5368,5644,5646],{"class":5370,"line":5645},8,[5368,5647,5649],{"emptyLinePlaceholder":5648},true,"\n",[5368,5651,5653],{"class":5370,"line":5652},9,[5368,5654,5655],{"class":5374},"# Проста мережа БЕЗ Batch Normalization\n",[5368,5657,5659,5663,5667,5670,5673,5675,5678],{"class":5370,"line":5658},10,[5368,5660,5662],{"class":5661},"su1O8","class",[5368,5664,5666],{"class":5665},"sN1BT"," SimpleNet",[5368,5668,5669],{"class":5381},"(",[5368,5671,5672],{"class":5665},"nn",[5368,5674,5497],{"class":5381},[5368,5676,5677],{"class":5665},"Module",[5368,5679,5680],{"class":5381},"):\n",[5368,5682,5684,5687,5691,5693,5696],{"class":5370,"line":5683},11,[5368,5685,5686],{"class":5661},"    def",[5368,5688,5690],{"class":5689},"s8Opu"," __init__",[5368,5692,5669],{"class":5381},[5368,5694,5695],{"class":5385},"self",[5368,5697,5680],{"class":5381},[5368,5699,5701,5704,5707,5709,5712,5715],{"class":5370,"line":5700},12,[5368,5702,5703],{"class":5665},"        super",[5368,5705,5706],{"class":5381},"(SimpleNet, ",[5368,5708,5695],{"class":5661},[5368,5710,5711],{"class":5381},").",[5368,5713,5714],{"class":5689},"__init__",[5368,5716,5717],{"class":5381},"()\n",[5368,5719,5721,5724,5727,5730,5732,5735],{"class":5370,"line":5720},13,[5368,5722,5723],{"class":5661},"        self",[5368,5725,5726],{"class":5381},".fc1 = nn.Linear(",[5368,5728,5729],{"class":5392},"784",[5368,5731,5396],{"class":5381},[5368,5733,5734],{"class":5392},"256",[5368,5736,5737],{"class":5381},")\n",[5368,5739,5741,5743,5746,5748,5750,5752],{"class":5370,"line":5740},14,[5368,5742,5723],{"class":5661},[5368,5744,5745],{"class":5381},".fc2 = nn.Linear(",[5368,5747,5734],{"class":5392},[5368,5749,5396],{"class":5381},[5368,5751,5734],{"class":5392},[5368,5753,5737],{"class":5381},[5368,5755,5757,5759,5762,5764,5766,5768,5771],{"class":5370,"line":5756},15,[5368,5758,5723],{"class":5661},[5368,5760,5761],{"class":5381},".fc3 = nn.Linear(",[5368,5763,5734],{"class":5392},[5368,5765,5396],{"class":5381},[5368,5767,5734],{"class":5392},[5368,5769,5770],{"class":5381},")  ",[5368,5772,5773],{"class":5374},"# Будемо моніторити цей шар\n",[5368,5775,5777,5779,5782,5784,5786,5789],{"class":5370,"line":5776},16,[5368,5778,5723],{"class":5661},[5368,5780,5781],{"class":5381},".fc4 = nn.Linear(",[5368,5783,5734],{"class":5392},[5368,5785,5396],{"class":5381},[5368,5787,5788],{"class":5392},"128",[5368,5790,5737],{"class":5381},[5368,5792,5794,5796,5799,5801,5803,5806],{"class":5370,"line":5793},17,[5368,5795,5723],{"class":5661},[5368,5797,5798],{"class":5381},".fc5 = nn.Linear(",[5368,5800,5788],{"class":5392},[5368,5802,5396],{"class":5381},[5368,5804,5805],{"class":5392},"10",[5368,5807,5737],{"class":5381},[5368,5809,5811,5813],{"class":5370,"line":5810},18,[5368,5812,5723],{"class":5661},[5368,5814,5815],{"class":5381},".relu = nn.ReLU()\n",[5368,5817,5819],{"class":5370,"line":5818},19,[5368,5820,5821],{"class":5381},"    \n",[5368,5823,5825,5827,5830,5832,5834,5836,5839,5841,5844,5847,5850],{"class":5370,"line":5824},20,[5368,5826,5686],{"class":5661},[5368,5828,5829],{"class":5689}," forward",[5368,5831,5669],{"class":5381},[5368,5833,5695],{"class":5385},[5368,5835,5396],{"class":5381},[5368,5837,5838],{"class":5385},"x",[5368,5840,5396],{"class":5381},[5368,5842,5843],{"class":5385},"return_layer3",[5368,5845,5846],{"class":5381},"=",[5368,5848,5849],{"class":5661},"False",[5368,5851,5680],{"class":5381},[5368,5853,5855,5858,5861,5864,5866],{"class":5370,"line":5854},21,[5368,5856,5857],{"class":5381},"        x = x.view(x.size(",[5368,5859,5860],{"class":5392},"0",[5368,5862,5863],{"class":5381},"), -",[5368,5865,5549],{"class":5392},[5368,5867,5737],{"class":5381},[5368,5869,5871,5874,5876,5879,5881],{"class":5370,"line":5870},22,[5368,5872,5873],{"class":5381},"        x = ",[5368,5875,5695],{"class":5661},[5368,5877,5878],{"class":5381},".relu(",[5368,5880,5695],{"class":5661},[5368,5882,5883],{"class":5381},".fc1(x))\n",[5368,5885,5887,5889,5891,5893,5895],{"class":5370,"line":5886},23,[5368,5888,5873],{"class":5381},[5368,5890,5695],{"class":5661},[5368,5892,5878],{"class":5381},[5368,5894,5695],{"class":5661},[5368,5896,5897],{"class":5381},".fc2(x))\n",[5368,5899,5901,5904],{"class":5370,"line":5900},24,[5368,5902,5903],{"class":5381},"        layer3_input = x.clone()  ",[5368,5905,5906],{"class":5374},"# Зберегти вхід 3-го шару\n",[5368,5908,5910,5912,5914,5916,5918],{"class":5370,"line":5909},25,[5368,5911,5873],{"class":5381},[5368,5913,5695],{"class":5661},[5368,5915,5878],{"class":5381},[5368,5917,5695],{"class":5661},[5368,5919,5920],{"class":5381},".fc3(x))\n",[5368,5922,5924,5926,5928,5930,5932],{"class":5370,"line":5923},26,[5368,5925,5873],{"class":5381},[5368,5927,5695],{"class":5661},[5368,5929,5878],{"class":5381},[5368,5931,5695],{"class":5661},[5368,5933,5934],{"class":5381},".fc4(x))\n",[5368,5936,5938,5940,5942],{"class":5370,"line":5937},27,[5368,5939,5873],{"class":5381},[5368,5941,5695],{"class":5661},[5368,5943,5944],{"class":5381},".fc5(x)\n",[5368,5946,5948],{"class":5370,"line":5947},28,[5368,5949,5950],{"class":5381},"        \n",[5368,5952,5954,5957],{"class":5370,"line":5953},29,[5368,5955,5956],{"class":5560},"        if",[5368,5958,5959],{"class":5381}," return_layer3:\n",[5368,5961,5963,5966],{"class":5370,"line":5962},30,[5368,5964,5965],{"class":5560},"            return",[5368,5967,5968],{"class":5381}," x, layer3_input\n",[5368,5970,5972,5975],{"class":5370,"line":5971},31,[5368,5973,5974],{"class":5560},"        return",[5368,5976,5977],{"class":5381}," x\n",[5368,5979,5981],{"class":5370,"line":5980},32,[5368,5982,5649],{"emptyLinePlaceholder":5648},[5368,5984,5986],{"class":5370,"line":5985},33,[5368,5987,5988],{"class":5374},"# Ініціалізація\n",[5368,5990,5992,5995,5999,6002,6005,6008,6011],{"class":5370,"line":5991},34,[5368,5993,5994],{"class":5381},"device = torch.device(",[5368,5996,5998],{"class":5997},"sbdoH","'cuda'",[5368,6000,6001],{"class":5560}," if",[5368,6003,6004],{"class":5381}," torch.cuda.is_available() ",[5368,6006,6007],{"class":5560},"else",[5368,6009,6010],{"class":5997}," 'cpu'",[5368,6012,5737],{"class":5381},[5368,6014,6016],{"class":5370,"line":6015},35,[5368,6017,6018],{"class":5381},"model = SimpleNet().to(device)\n",[5368,6020,6022],{"class":5370,"line":6021},36,[5368,6023,6024],{"class":5381},"criterion = nn.CrossEntropyLoss()\n",[5368,6026,6028,6031,6034,6036,6039,6041,6044,6046,6049],{"class":5370,"line":6027},37,[5368,6029,6030],{"class":5381},"optimizer = optim.SGD(model.parameters(), ",[5368,6032,6033],{"class":5385},"lr",[5368,6035,5846],{"class":5381},[5368,6037,6038],{"class":5392},"0.01",[5368,6040,5396],{"class":5381},[5368,6042,6043],{"class":5385},"momentum",[5368,6045,5846],{"class":5381},[5368,6047,6048],{"class":5392},"0.9",[5368,6050,5737],{"class":5381},[5368,6052,6054],{"class":5370,"line":6053},38,[5368,6055,5649],{"emptyLinePlaceholder":5648},[5368,6057,6059],{"class":5370,"line":6058},39,[5368,6060,6061],{"class":5374},"# MNIST DataLoader\n",[5368,6063,6065],{"class":5370,"line":6064},40,[5368,6066,6067],{"class":5381},"transform = transforms.Compose([\n",[5368,6069,6071],{"class":5370,"line":6070},41,[5368,6072,6073],{"class":5381},"    transforms.ToTensor(),\n",[5368,6075,6077,6080,6083,6086,6089],{"class":5370,"line":6076},42,[5368,6078,6079],{"class":5381},"    transforms.Normalize((",[5368,6081,6082],{"class":5392},"0.1307",[5368,6084,6085],{"class":5381},",), (",[5368,6087,6088],{"class":5392},"0.3081",[5368,6090,6091],{"class":5381},",))\n",[5368,6093,6095],{"class":5370,"line":6094},43,[5368,6096,5431],{"class":5381},[5368,6098,6100,6103,6106,6108,6111,6113,6116,6118,6121,6123,6125,6127,6130],{"class":5370,"line":6099},44,[5368,6101,6102],{"class":5381},"train_dataset = datasets.MNIST(",[5368,6104,6105],{"class":5997},"'.\u002Fdata'",[5368,6107,5396],{"class":5381},[5368,6109,6110],{"class":5385},"train",[5368,6112,5846],{"class":5381},[5368,6114,6115],{"class":5661},"True",[5368,6117,5396],{"class":5381},[5368,6119,6120],{"class":5385},"download",[5368,6122,5846],{"class":5381},[5368,6124,6115],{"class":5661},[5368,6126,5396],{"class":5381},[5368,6128,6129],{"class":5385},"transform",[5368,6131,6132],{"class":5381},"=transform)\n",[5368,6134,6136,6139,6142,6144,6146,6148,6151,6153,6155],{"class":5370,"line":6135},45,[5368,6137,6138],{"class":5381},"train_loader = DataLoader(train_dataset, ",[5368,6140,6141],{"class":5385},"batch_size",[5368,6143,5846],{"class":5381},[5368,6145,5788],{"class":5392},[5368,6147,5396],{"class":5381},[5368,6149,6150],{"class":5385},"shuffle",[5368,6152,5846],{"class":5381},[5368,6154,6115],{"class":5661},[5368,6156,5737],{"class":5381},[5368,6158,6160],{"class":5370,"line":6159},46,[5368,6161,5649],{"emptyLinePlaceholder":5648},[5368,6163,6165],{"class":5370,"line":6164},47,[5368,6166,6167],{"class":5374},"# Збереження статистики розподілу входів 3-го шару\n",[5368,6169,6171],{"class":5370,"line":6170},48,[5368,6172,6173],{"class":5381},"layer3_means = []\n",[5368,6175,6177],{"class":5370,"line":6176},49,[5368,6178,6179],{"class":5381},"layer3_stds = []\n",[5368,6181,6183],{"class":5370,"line":6182},50,[5368,6184,5649],{"emptyLinePlaceholder":5648},[5368,6186,6188],{"class":5370,"line":6187},51,[5368,6189,6190],{"class":5381},"model.train()\n",[5368,6192,6194,6197,6200,6203,6206],{"class":5370,"line":6193},52,[5368,6195,6196],{"class":5560},"for",[5368,6198,6199],{"class":5381}," iteration, (images, labels) ",[5368,6201,6202],{"class":5560},"in",[5368,6204,6205],{"class":5689}," enumerate",[5368,6207,6208],{"class":5381},"(train_loader):\n",[5368,6210,6212,6215,6218,6221,6224],{"class":5370,"line":6211},53,[5368,6213,6214],{"class":5560},"    if",[5368,6216,6217],{"class":5381}," iteration >= ",[5368,6219,6220],{"class":5392},"100",[5368,6222,6223],{"class":5381},":  ",[5368,6225,6226],{"class":5374},"# Перші 100 ітерацій\n",[5368,6228,6230],{"class":5370,"line":6229},54,[5368,6231,6232],{"class":5560},"        break\n",[5368,6234,6236],{"class":5370,"line":6235},55,[5368,6237,5821],{"class":5381},[5368,6239,6241],{"class":5370,"line":6240},56,[5368,6242,6243],{"class":5381},"    images, labels = images.to(device), labels.to(device)\n",[5368,6245,6247],{"class":5370,"line":6246},57,[5368,6248,5821],{"class":5381},[5368,6250,6252],{"class":5370,"line":6251},58,[5368,6253,6254],{"class":5374},"    # Forward з збереженням активацій\n",[5368,6256,6258,6261,6263,6265,6267],{"class":5370,"line":6257},59,[5368,6259,6260],{"class":5381},"    outputs, layer3_input = model(images, ",[5368,6262,5843],{"class":5385},[5368,6264,5846],{"class":5381},[5368,6266,6115],{"class":5661},[5368,6268,5737],{"class":5381},[5368,6270,6272],{"class":5370,"line":6271},60,[5368,6273,6274],{"class":5381},"    loss = criterion(outputs, labels)\n",[5368,6276,6278],{"class":5370,"line":6277},61,[5368,6279,5821],{"class":5381},[5368,6281,6283],{"class":5370,"line":6282},62,[5368,6284,6285],{"class":5374},"    # Backward та оптимізація\n",[5368,6287,6289],{"class":5370,"line":6288},63,[5368,6290,6291],{"class":5381},"    optimizer.zero_grad()\n",[5368,6293,6295],{"class":5370,"line":6294},64,[5368,6296,6297],{"class":5381},"    loss.backward()\n",[5368,6299,6301],{"class":5370,"line":6300},65,[5368,6302,6303],{"class":5381},"    optimizer.step()\n",[5368,6305,6307],{"class":5370,"line":6306},66,[5368,6308,5821],{"class":5381},[5368,6310,6312],{"class":5370,"line":6311},67,[5368,6313,6314],{"class":5374},"    # Статистика входу 3-го шару\n",[5368,6316,6318,6321],{"class":5370,"line":6317},68,[5368,6319,6320],{"class":5560},"    with",[5368,6322,6323],{"class":5381}," torch.no_grad():\n",[5368,6325,6327],{"class":5370,"line":6326},69,[5368,6328,6329],{"class":5381},"        mean = layer3_input.mean().item()\n",[5368,6331,6333],{"class":5370,"line":6332},70,[5368,6334,6335],{"class":5381},"        std = layer3_input.std().item()\n",[5368,6337,6339],{"class":5370,"line":6338},71,[5368,6340,6341],{"class":5381},"        layer3_means.append(mean)\n",[5368,6343,6345],{"class":5370,"line":6344},72,[5368,6346,6347],{"class":5381},"        layer3_stds.append(std)\n",[5368,6349,6351],{"class":5370,"line":6350},73,[5368,6352,5649],{"emptyLinePlaceholder":5648},[5368,6354,6356,6359,6361,6364,6367,6370,6373,6376,6379,6382],{"class":5370,"line":6355},74,[5368,6357,6358],{"class":5689},"print",[5368,6360,5669],{"class":5381},[5368,6362,6363],{"class":5661},"f",[5368,6365,6366],{"class":5997},"\"✅ Відстежено ",[5368,6368,6369],{"class":5661},"{",[5368,6371,6372],{"class":5689},"len",[5368,6374,6375],{"class":5381},"(layer3_means)",[5368,6377,6378],{"class":5661},"}",[5368,6380,6381],{"class":5997}," ітерацій навчання\"",[5368,6383,5737],{"class":5381},[5368,6385,6387,6389,6391,6393,6396,6398,6401,6403,6406,6409,6412],{"class":5370,"line":6386},75,[5368,6388,6358],{"class":5689},[5368,6390,5669],{"class":5381},[5368,6392,6363],{"class":5661},[5368,6394,6395],{"class":5997},"\"   Початкове середнє входу 3-го шару: ",[5368,6397,6369],{"class":5661},[5368,6399,6400],{"class":5381},"layer3_means[",[5368,6402,5860],{"class":5392},[5368,6404,6405],{"class":5381},"]",[5368,6407,6408],{"class":5661},":.4f}",[5368,6410,6411],{"class":5997},"\"",[5368,6413,5737],{"class":5381},[5368,6415,6417,6419,6421,6423,6426,6428,6431,6433,6435,6437,6439],{"class":5370,"line":6416},76,[5368,6418,6358],{"class":5689},[5368,6420,5669],{"class":5381},[5368,6422,6363],{"class":5661},[5368,6424,6425],{"class":5997},"\"   Фінальне середнє входу 3-го шару:  ",[5368,6427,6369],{"class":5661},[5368,6429,6430],{"class":5381},"layer3_means[-",[5368,6432,5549],{"class":5392},[5368,6434,6405],{"class":5381},[5368,6436,6408],{"class":5661},[5368,6438,6411],{"class":5997},[5368,6440,5737],{"class":5381},[5368,6442,6444,6446,6448,6450,6453,6455,6458,6461,6463,6466,6468,6471,6473,6475],{"class":5370,"line":6443},77,[5368,6445,6358],{"class":5689},[5368,6447,5669],{"class":5381},[5368,6449,6363],{"class":5661},[5368,6451,6452],{"class":5997},"\"   Зміна: ",[5368,6454,6369],{"class":5661},[5368,6456,6457],{"class":5689},"abs",[5368,6459,6460],{"class":5381},"(layer3_means[-",[5368,6462,5549],{"class":5392},[5368,6464,6465],{"class":5381},"] - layer3_means[",[5368,6467,5860],{"class":5392},[5368,6469,6470],{"class":5381},"])",[5368,6472,6408],{"class":5661},[5368,6474,6411],{"class":5997},[5368,6476,5737],{"class":5381},[6478,6479,6480,6486,6549],"template",{"v-slot:output":5363},[5191,6481,6482,6483],{},"✅ ",[5195,6484,6485],{},"Відстежено 100 ітерацій навчання",[6487,6488,6489,6509],"table",{},[6490,6491,6492],"thead",{},[6493,6494,6495,6500,6503,6506],"tr",{},[6496,6497,6499],"th",{"align":6498},"left","Метрика",[6496,6501,6502],{"align":6498},"Початок (ітерація 1)",[6496,6504,6505],{"align":6498},"Кінець (ітерація 100)",[6496,6507,6508],{"align":6498},"Зміна",[6510,6511,6512,6531],"tbody",{},[6493,6513,6514,6520,6523,6526],{},[6515,6516,6517],"td",{"align":6498},[5195,6518,6519],{},"Середнє (μ)",[6515,6521,6522],{"align":6498},"0.2847",[6515,6524,6525],{"align":6498},"0.6125",[6515,6527,6528],{"align":6498},[5195,6529,6530],{},"+0.3278",[6493,6532,6533,6538,6541,6544],{},[6515,6534,6535],{"align":6498},[5195,6536,6537],{},"Стандартне відхилення (σ)",[6515,6539,6540],{"align":6498},"0.3521",[6515,6542,6543],{"align":6498},"0.4892",[6515,6545,6546],{"align":6498},[5195,6547,6548],{},"+0.1371",[5191,6550,6551,6552,6555],{},"⚠️ Розподіл входів 3-го шару ",[5195,6553,6554],{},"значно змінився"," протягом лише 100 ітерацій!",[5537,6557,6560,7140],{"execution-count":6558,"execution-time":6559},"2","0.8s",[5358,6561,6563],{"className":5360,"code":6562,"language":5362,"meta":5363,"style":5363},"# Візуалізація дрейфу розподілу\nfig, axes = plt.subplots(1, 2, figsize=(16, 5))\n\n# Графік 1: Зміна середнього\nax1 = axes[0]\nax1.plot(range(len(layer3_means)), layer3_means, \n         color='#3b82f6', linewidth=2, label='Mean (μ)')\nax1.axhline(layer3_means[0], color='gray', linestyle='--', \n            alpha=0.5, label=f'Початкове μ = {layer3_means[0]:.3f}')\nax1.fill_between(range(len(layer3_means)), \n                 layer3_means[0], layer3_means,\n                 alpha=0.2, color='#3b82f6')\nax1.set_xlabel('Ітерація', fontsize=12)\nax1.set_ylabel('Середнє значення входу', fontsize=12)\nax1.set_title('Дрейф середнього (μ) протягом навчання', \n              fontsize=14, fontweight='bold')\nax1.legend(fontsize=11)\nax1.grid(alpha=0.3)\n\n# Графік 2: Зміна стандартного відхилення\nax2 = axes[1]\nax2.plot(range(len(layer3_stds)), layer3_stds, \n         color='#ef4444', linewidth=2, label='Std (σ)')\nax2.axhline(layer3_stds[0], color='gray', linestyle='--', \n            alpha=0.5, label=f'Початкове σ = {layer3_stds[0]:.3f}')\nax2.fill_between(range(len(layer3_stds)), \n                 layer3_stds[0], layer3_stds,\n                 alpha=0.2, color='#ef4444')\nax2.set_xlabel('Ітерація', fontsize=12)\nax2.set_ylabel('Стандартне відхилення входу', fontsize=12)\nax2.set_title('Дрейф дисперсії (σ²) протягом навчання', \n              fontsize=14, fontweight='bold')\nax2.legend(fontsize=11)\nax2.grid(alpha=0.3)\n\nplt.tight_layout()\nplt.show()\n",[5365,6564,6565,6570,6600,6604,6609,6619,6634,6665,6696,6733,6747,6757,6777,6797,6815,6825,6847,6861,6876,6880,6885,6894,6908,6936,6961,6995,7009,7019,7037,7054,7072,7082,7100,7113,7126,7130,7135],{"__ignoreMap":5363},[5368,6566,6567],{"class":5370,"line":5371},[5368,6568,6569],{"class":5374},"# Візуалізація дрейфу розподілу\n",[5368,6571,6572,6575,6577,6579,6581,6583,6586,6589,6592,6594,6597],{"class":5370,"line":5378},[5368,6573,6574],{"class":5381},"fig, axes = plt.subplots(",[5368,6576,5549],{"class":5392},[5368,6578,5396],{"class":5381},[5368,6580,6558],{"class":5392},[5368,6582,5396],{"class":5381},[5368,6584,6585],{"class":5385},"figsize",[5368,6587,6588],{"class":5381},"=(",[5368,6590,6591],{"class":5392},"16",[5368,6593,5396],{"class":5381},[5368,6595,6596],{"class":5392},"5",[5368,6598,6599],{"class":5381},"))\n",[5368,6601,6602],{"class":5370,"line":5410},[5368,6603,5649],{"emptyLinePlaceholder":5648},[5368,6605,6606],{"class":5370,"line":5592},[5368,6607,6608],{"class":5374},"# Графік 1: Зміна середнього\n",[5368,6610,6611,6614,6616],{"class":5370,"line":5606},[5368,6612,6613],{"class":5381},"ax1 = axes[",[5368,6615,5860],{"class":5392},[5368,6617,6618],{"class":5381},"]\n",[5368,6620,6621,6624,6627,6629,6631],{"class":5370,"line":5619},[5368,6622,6623],{"class":5381},"ax1.plot(",[5368,6625,6626],{"class":5689},"range",[5368,6628,5669],{"class":5381},[5368,6630,6372],{"class":5689},[5368,6632,6633],{"class":5381},"(layer3_means)), layer3_means, \n",[5368,6635,6636,6639,6641,6644,6646,6649,6651,6653,6655,6658,6660,6663],{"class":5370,"line":5632},[5368,6637,6638],{"class":5385},"         color",[5368,6640,5846],{"class":5381},[5368,6642,6643],{"class":5997},"'#3b82f6'",[5368,6645,5396],{"class":5381},[5368,6647,6648],{"class":5385},"linewidth",[5368,6650,5846],{"class":5381},[5368,6652,6558],{"class":5392},[5368,6654,5396],{"class":5381},[5368,6656,6657],{"class":5385},"label",[5368,6659,5846],{"class":5381},[5368,6661,6662],{"class":5997},"'Mean (μ)'",[5368,6664,5737],{"class":5381},[5368,6666,6667,6670,6672,6675,6678,6680,6683,6685,6688,6690,6693],{"class":5370,"line":5645},[5368,6668,6669],{"class":5381},"ax1.axhline(layer3_means[",[5368,6671,5860],{"class":5392},[5368,6673,6674],{"class":5381},"], ",[5368,6676,6677],{"class":5385},"color",[5368,6679,5846],{"class":5381},[5368,6681,6682],{"class":5997},"'gray'",[5368,6684,5396],{"class":5381},[5368,6686,6687],{"class":5385},"linestyle",[5368,6689,5846],{"class":5381},[5368,6691,6692],{"class":5997},"'--'",[5368,6694,6695],{"class":5381},", \n",[5368,6697,6698,6701,6703,6706,6708,6710,6712,6714,6717,6719,6721,6723,6725,6728,6731],{"class":5370,"line":5652},[5368,6699,6700],{"class":5385},"            alpha",[5368,6702,5846],{"class":5381},[5368,6704,6705],{"class":5392},"0.5",[5368,6707,5396],{"class":5381},[5368,6709,6657],{"class":5385},[5368,6711,5846],{"class":5381},[5368,6713,6363],{"class":5661},[5368,6715,6716],{"class":5997},"'Початкове μ = ",[5368,6718,6369],{"class":5661},[5368,6720,6400],{"class":5381},[5368,6722,5860],{"class":5392},[5368,6724,6405],{"class":5381},[5368,6726,6727],{"class":5661},":.3f}",[5368,6729,6730],{"class":5997},"'",[5368,6732,5737],{"class":5381},[5368,6734,6735,6738,6740,6742,6744],{"class":5370,"line":5658},[5368,6736,6737],{"class":5381},"ax1.fill_between(",[5368,6739,6626],{"class":5689},[5368,6741,5669],{"class":5381},[5368,6743,6372],{"class":5689},[5368,6745,6746],{"class":5381},"(layer3_means)), \n",[5368,6748,6749,6752,6754],{"class":5370,"line":5683},[5368,6750,6751],{"class":5381},"                 layer3_means[",[5368,6753,5860],{"class":5392},[5368,6755,6756],{"class":5381},"], layer3_means,\n",[5368,6758,6759,6762,6764,6767,6769,6771,6773,6775],{"class":5370,"line":5700},[5368,6760,6761],{"class":5385},"                 alpha",[5368,6763,5846],{"class":5381},[5368,6765,6766],{"class":5392},"0.2",[5368,6768,5396],{"class":5381},[5368,6770,6677],{"class":5385},[5368,6772,5846],{"class":5381},[5368,6774,6643],{"class":5997},[5368,6776,5737],{"class":5381},[5368,6778,6779,6782,6785,6787,6790,6792,6795],{"class":5370,"line":5720},[5368,6780,6781],{"class":5381},"ax1.set_xlabel(",[5368,6783,6784],{"class":5997},"'Ітерація'",[5368,6786,5396],{"class":5381},[5368,6788,6789],{"class":5385},"fontsize",[5368,6791,5846],{"class":5381},[5368,6793,6794],{"class":5392},"12",[5368,6796,5737],{"class":5381},[5368,6798,6799,6802,6805,6807,6809,6811,6813],{"class":5370,"line":5740},[5368,6800,6801],{"class":5381},"ax1.set_ylabel(",[5368,6803,6804],{"class":5997},"'Середнє значення входу'",[5368,6806,5396],{"class":5381},[5368,6808,6789],{"class":5385},[5368,6810,5846],{"class":5381},[5368,6812,6794],{"class":5392},[5368,6814,5737],{"class":5381},[5368,6816,6817,6820,6823],{"class":5370,"line":5756},[5368,6818,6819],{"class":5381},"ax1.set_title(",[5368,6821,6822],{"class":5997},"'Дрейф середнього (μ) протягом навчання'",[5368,6824,6695],{"class":5381},[5368,6826,6827,6830,6832,6835,6837,6840,6842,6845],{"class":5370,"line":5776},[5368,6828,6829],{"class":5385},"              fontsize",[5368,6831,5846],{"class":5381},[5368,6833,6834],{"class":5392},"14",[5368,6836,5396],{"class":5381},[5368,6838,6839],{"class":5385},"fontweight",[5368,6841,5846],{"class":5381},[5368,6843,6844],{"class":5997},"'bold'",[5368,6846,5737],{"class":5381},[5368,6848,6849,6852,6854,6856,6859],{"class":5370,"line":5793},[5368,6850,6851],{"class":5381},"ax1.legend(",[5368,6853,6789],{"class":5385},[5368,6855,5846],{"class":5381},[5368,6857,6858],{"class":5392},"11",[5368,6860,5737],{"class":5381},[5368,6862,6863,6866,6869,6871,6874],{"class":5370,"line":5810},[5368,6864,6865],{"class":5381},"ax1.grid(",[5368,6867,6868],{"class":5385},"alpha",[5368,6870,5846],{"class":5381},[5368,6872,6873],{"class":5392},"0.3",[5368,6875,5737],{"class":5381},[5368,6877,6878],{"class":5370,"line":5818},[5368,6879,5649],{"emptyLinePlaceholder":5648},[5368,6881,6882],{"class":5370,"line":5824},[5368,6883,6884],{"class":5374},"# Графік 2: Зміна стандартного відхилення\n",[5368,6886,6887,6890,6892],{"class":5370,"line":5854},[5368,6888,6889],{"class":5381},"ax2 = axes[",[5368,6891,5549],{"class":5392},[5368,6893,6618],{"class":5381},[5368,6895,6896,6899,6901,6903,6905],{"class":5370,"line":5870},[5368,6897,6898],{"class":5381},"ax2.plot(",[5368,6900,6626],{"class":5689},[5368,6902,5669],{"class":5381},[5368,6904,6372],{"class":5689},[5368,6906,6907],{"class":5381},"(layer3_stds)), layer3_stds, \n",[5368,6909,6910,6912,6914,6917,6919,6921,6923,6925,6927,6929,6931,6934],{"class":5370,"line":5886},[5368,6911,6638],{"class":5385},[5368,6913,5846],{"class":5381},[5368,6915,6916],{"class":5997},"'#ef4444'",[5368,6918,5396],{"class":5381},[5368,6920,6648],{"class":5385},[5368,6922,5846],{"class":5381},[5368,6924,6558],{"class":5392},[5368,6926,5396],{"class":5381},[5368,6928,6657],{"class":5385},[5368,6930,5846],{"class":5381},[5368,6932,6933],{"class":5997},"'Std (σ)'",[5368,6935,5737],{"class":5381},[5368,6937,6938,6941,6943,6945,6947,6949,6951,6953,6955,6957,6959],{"class":5370,"line":5900},[5368,6939,6940],{"class":5381},"ax2.axhline(layer3_stds[",[5368,6942,5860],{"class":5392},[5368,6944,6674],{"class":5381},[5368,6946,6677],{"class":5385},[5368,6948,5846],{"class":5381},[5368,6950,6682],{"class":5997},[5368,6952,5396],{"class":5381},[5368,6954,6687],{"class":5385},[5368,6956,5846],{"class":5381},[5368,6958,6692],{"class":5997},[5368,6960,6695],{"class":5381},[5368,6962,6963,6965,6967,6969,6971,6973,6975,6977,6980,6982,6985,6987,6989,6991,6993],{"class":5370,"line":5909},[5368,6964,6700],{"class":5385},[5368,6966,5846],{"class":5381},[5368,6968,6705],{"class":5392},[5368,6970,5396],{"class":5381},[5368,6972,6657],{"class":5385},[5368,6974,5846],{"class":5381},[5368,6976,6363],{"class":5661},[5368,6978,6979],{"class":5997},"'Початкове σ = ",[5368,6981,6369],{"class":5661},[5368,6983,6984],{"class":5381},"layer3_stds[",[5368,6986,5860],{"class":5392},[5368,6988,6405],{"class":5381},[5368,6990,6727],{"class":5661},[5368,6992,6730],{"class":5997},[5368,6994,5737],{"class":5381},[5368,6996,6997,7000,7002,7004,7006],{"class":5370,"line":5923},[5368,6998,6999],{"class":5381},"ax2.fill_between(",[5368,7001,6626],{"class":5689},[5368,7003,5669],{"class":5381},[5368,7005,6372],{"class":5689},[5368,7007,7008],{"class":5381},"(layer3_stds)), \n",[5368,7010,7011,7014,7016],{"class":5370,"line":5937},[5368,7012,7013],{"class":5381},"                 layer3_stds[",[5368,7015,5860],{"class":5392},[5368,7017,7018],{"class":5381},"], layer3_stds,\n",[5368,7020,7021,7023,7025,7027,7029,7031,7033,7035],{"class":5370,"line":5947},[5368,7022,6761],{"class":5385},[5368,7024,5846],{"class":5381},[5368,7026,6766],{"class":5392},[5368,7028,5396],{"class":5381},[5368,7030,6677],{"class":5385},[5368,7032,5846],{"class":5381},[5368,7034,6916],{"class":5997},[5368,7036,5737],{"class":5381},[5368,7038,7039,7042,7044,7046,7048,7050,7052],{"class":5370,"line":5953},[5368,7040,7041],{"class":5381},"ax2.set_xlabel(",[5368,7043,6784],{"class":5997},[5368,7045,5396],{"class":5381},[5368,7047,6789],{"class":5385},[5368,7049,5846],{"class":5381},[5368,7051,6794],{"class":5392},[5368,7053,5737],{"class":5381},[5368,7055,7056,7059,7062,7064,7066,7068,7070],{"class":5370,"line":5962},[5368,7057,7058],{"class":5381},"ax2.set_ylabel(",[5368,7060,7061],{"class":5997},"'Стандартне відхилення входу'",[5368,7063,5396],{"class":5381},[5368,7065,6789],{"class":5385},[5368,7067,5846],{"class":5381},[5368,7069,6794],{"class":5392},[5368,7071,5737],{"class":5381},[5368,7073,7074,7077,7080],{"class":5370,"line":5971},[5368,7075,7076],{"class":5381},"ax2.set_title(",[5368,7078,7079],{"class":5997},"'Дрейф дисперсії (σ²) протягом навчання'",[5368,7081,6695],{"class":5381},[5368,7083,7084,7086,7088,7090,7092,7094,7096,7098],{"class":5370,"line":5980},[5368,7085,6829],{"class":5385},[5368,7087,5846],{"class":5381},[5368,7089,6834],{"class":5392},[5368,7091,5396],{"class":5381},[5368,7093,6839],{"class":5385},[5368,7095,5846],{"class":5381},[5368,7097,6844],{"class":5997},[5368,7099,5737],{"class":5381},[5368,7101,7102,7105,7107,7109,7111],{"class":5370,"line":5985},[5368,7103,7104],{"class":5381},"ax2.legend(",[5368,7106,6789],{"class":5385},[5368,7108,5846],{"class":5381},[5368,7110,6858],{"class":5392},[5368,7112,5737],{"class":5381},[5368,7114,7115,7118,7120,7122,7124],{"class":5370,"line":5991},[5368,7116,7117],{"class":5381},"ax2.grid(",[5368,7119,6868],{"class":5385},[5368,7121,5846],{"class":5381},[5368,7123,6873],{"class":5392},[5368,7125,5737],{"class":5381},[5368,7127,7128],{"class":5370,"line":6015},[5368,7129,5649],{"emptyLinePlaceholder":5648},[5368,7131,7132],{"class":5370,"line":6021},[5368,7133,7134],{"class":5381},"plt.tight_layout()\n",[5368,7136,7137],{"class":5370,"line":6027},[5368,7138,7139],{"class":5381},"plt.show()\n",[6478,7141,7142],{"v-slot:output":5363},[7143,7144],"img",{"alt":7145,"className":7146,"src":7148},"Internal Covariate Shift: розподіл входів 3-го шару дрейфує протягом навчання",[7147],"diagram-img","\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fbatch-normalization\u002F01.png",[7150,7151,7152,7157],"warning",{},[5191,7153,7154],{},[5195,7155,7156],{},"Наслідки Internal Covariate Shift:",[7158,7159,7160,7166,7172,7178],"ol",{},[5250,7161,7162,7165],{},[5195,7163,7164],{},"Повільна конвергенція:"," Кожен шар постійно адаптується до рухомого розподілу входів замість навчання стабільних ознак.",[5250,7167,7168,7171],{},[5195,7169,7170],{},"Обмеження learning rate:"," Великий LR призводить до нестабільності, бо різкі зміни нижніх шарів «ламають» верхні.",[5250,7173,7174,7177],{},[5195,7175,7176],{},"Чутливість до ініціалізації:"," Погана ініціалізація посилює дрейф розподілів, роблячи навчання майже неможливим.",[5250,7179,7180,7183],{},[5195,7181,7182],{},"Проблема gradient saturation:"," Якщо активації дрейфують у зони насичення (для sigmoid\u002Ftanh), градієнти зникають.",[5304,7185],{},[5186,7187,7189],{"id":7188},"розвязання-batch-normalization","Розв'язання: Batch Normalization",[5191,7191,7192,7193,7196],{},"Ідея Batch Normalization елегантно проста: ",[5195,7194,7195],{},"нормалізувати входи кожного шару до стандартного розподілу"," перед застосуванням активації. Це стабілізує розподіл та дозволяє кожному шару вчитися незалежніше від інших.",[5322,7198,7200],{"id":7199},"математика-batch-normalization","Математика Batch Normalization",[5191,7202,7203,7204,7207,7208,7211],{},"Розглянемо міні-батч із ",[5333,7205],{"tex":7206,":inline":5336},"m"," прикладів. Нехай ",[5333,7209],{"tex":7210,":inline":5336},"\\mathbf{x} = \\{x_1, x_2, \\ldots, x_m\\}"," — входи для поточного шару (або одного нейрона, якщо розглядаємо поелементно).",[5191,7213,7214],{},[5195,7215,7216],{},"Крок 1. Обчислення статистики батчу:",[5333,7218],{"tex":7219},"\\mu_\\mathcal{B} = \\frac{1}{m} \\sum_{i=1}^{m} x_i",[5333,7221],{"tex":7222},"\\sigma^2_\\mathcal{B} = \\frac{1}{m} \\sum_{i=1}^{m} (x_i - \\mu_\\mathcal{B})^2",[5191,7224,7225],{},[5195,7226,7227],{},"Крок 2. Нормалізація:",[5333,7229],{"tex":7230},"\\hat{x}_i = \\frac{x_i - \\mu_\\mathcal{B}}{\\sqrt{\\sigma^2_\\mathcal{B} + \\epsilon}}",[5191,7232,7233,7234,7237,7238,7241],{},"Де ",[5333,7235],{"tex":7236,":inline":5336},"\\epsilon"," — мала константа (зазвичай ",[5333,7239],{"tex":7240,":inline":5336},"10^{-5}",") для числової стабільності (уникнення ділення на нуль).",[5191,7243,7244,7245,5489,7248,7251,7252,7255,7256,5497],{},"Після цього кроку ",[5195,7246,7247],{},"всі",[5333,7249],{"tex":7250,":inline":5336},"\\hat{x}_i"," мають приблизно ",[5333,7253],{"tex":7254,":inline":5336},"\\mu = 0"," та ",[5333,7257],{"tex":7258,":inline":5336},"\\sigma^2 = 1",[5191,7260,7261],{},[5195,7262,7263],{},"Крок 3. Масштабування та зсув (learnable parameters):",[5333,7265],{"tex":7266},"y_i = \\gamma \\hat{x}_i + \\beta",[5191,7268,7269],{},"Де:",[5247,7271,7272,7286],{},[5250,7273,7274,7277,7278,7282,7283],{},[5333,7275],{"tex":7276,":inline":5336},"\\gamma"," (",[7279,7280,7281],"em",{},"gamma",") — ",[5195,7284,7285],{},"навчуваний параметр масштабування",[5250,7287,7288,7277,7291,7282,7294],{},[5333,7289],{"tex":7290,":inline":5336},"\\beta",[7279,7292,7293],{},"beta",[5195,7295,7296],{},"навчуваний параметр зсуву",[5191,7298,7299],{},[5195,7300,7301],{},"Чому потрібні γ та β?",[5191,7303,7304,7305,7308,7309,7312,7313,5497],{},"На перший погляд, нормалізація до μ=0, σ²=1 виглядає ідеально. Але що, якщо ",[5195,7306,7307],{},"оптимальний розподіл для цього шару — не стандартний","? Наприклад, sigmoid активація працює найкраще у діапазоні ",[5368,7310,7311],{},"-2, 2",", а не ",[5368,7314,7315],{},"-1, 1",[5191,7317,7318,7319,7322,7323,7255,7326,7329],{},"Параметри γ та β дозволяють мережі ",[5195,7320,7321],{},"відновити вихідний розподіл, якщо це необхідно",". Якщо мережа навчить ",[5333,7324],{"tex":7325,":inline":5336},"\\gamma = \\sqrt{\\sigma^2_\\mathcal{B}}",[5333,7327],{"tex":7328,":inline":5336},"\\beta = \\mu_\\mathcal{B}",", то:",[5333,7331],{"tex":7332},"y_i = \\gamma \\hat{x}_i + \\beta = \\sqrt{\\sigma^2_\\mathcal{B}} \\cdot \\frac{x_i - \\mu_\\mathcal{B}}{\\sqrt{\\sigma^2_\\mathcal{B}}} + \\mu_\\mathcal{B} = x_i",[5191,7334,7335,7336,7339,7340,7343],{},"Тобто Batch Normalization ",[5195,7337,7338],{},"відміняється",". Це дає мережі ",[5195,7341,7342],{},"свободу вибору",": використовувати нормалізацію повністю, частково або взагалі не використовувати.",[7345,7346,7348],"plant-uml",{"alt":7347},"Схема Batch Normalization шару",[5358,7349,7353],{"className":7350,"code":7351,"language":7352,"meta":5363,"style":5363},"language-plantuml shiki shiki-themes light-plus dark-plus dark-plus","@startuml\nskinparam style plain\nskinparam backgroundColor #FFFFFF\nskinparam defaultFontName \"Arial\"\n\nrectangle \"Вхід міні-батчу\\nx₁, x₂, ..., xₘ\" as input #DBEAFE\n\nrectangle \"Обчислення статистики\" as stats #FEF3C7 {\n  rectangle \"μ = (1\u002Fm)Σxᵢ\" as mean\n  rectangle \"σ² = (1\u002Fm)Σ(xᵢ-μ)²\" as var\n}\n\nrectangle \"Нормалізація\" as norm #DCFCE7 {\n  rectangle \"x̂ᵢ = (xᵢ - μ) \u002F √(σ² + ε)\" as normalize\n}\n\nrectangle \"Масштабування та зсув\" as scale #E0E7FF {\n  rectangle \"yᵢ = γx̂ᵢ + β\" as transform\n  note right of transform\n    γ, β — навчувані параметри\n    (оновлюються через backprop)\n  end note\n}\n\nrectangle \"Вихід\\ny₁, y₂, ..., yₘ\" as output #DCFCE7\n\ninput -down-> stats\nstats -down-> norm\nnorm -down-> scale\nscale -down-> output\n\n@enduml\n","plantuml",[5365,7354,7355,7360,7365,7370,7375,7379,7384,7388,7393,7398,7403,7408,7412,7417,7422,7426,7430,7435,7440,7445,7450,7455,7460,7464,7468,7473,7477,7482,7487,7492,7497,7501],{"__ignoreMap":5363},[5368,7356,7357],{"class":5370,"line":5371},[5368,7358,7359],{},"@startuml\n",[5368,7361,7362],{"class":5370,"line":5378},[5368,7363,7364],{},"skinparam style plain\n",[5368,7366,7367],{"class":5370,"line":5410},[5368,7368,7369],{},"skinparam backgroundColor #FFFFFF\n",[5368,7371,7372],{"class":5370,"line":5592},[5368,7373,7374],{},"skinparam defaultFontName \"Arial\"\n",[5368,7376,7377],{"class":5370,"line":5606},[5368,7378,5649],{"emptyLinePlaceholder":5648},[5368,7380,7381],{"class":5370,"line":5619},[5368,7382,7383],{},"rectangle \"Вхід міні-батчу\\nx₁, x₂, ..., xₘ\" as input #DBEAFE\n",[5368,7385,7386],{"class":5370,"line":5632},[5368,7387,5649],{"emptyLinePlaceholder":5648},[5368,7389,7390],{"class":5370,"line":5645},[5368,7391,7392],{},"rectangle \"Обчислення статистики\" as stats #FEF3C7 {\n",[5368,7394,7395],{"class":5370,"line":5652},[5368,7396,7397],{},"  rectangle \"μ = (1\u002Fm)Σxᵢ\" as mean\n",[5368,7399,7400],{"class":5370,"line":5658},[5368,7401,7402],{},"  rectangle \"σ² = (1\u002Fm)Σ(xᵢ-μ)²\" as var\n",[5368,7404,7405],{"class":5370,"line":5683},[5368,7406,7407],{},"}\n",[5368,7409,7410],{"class":5370,"line":5700},[5368,7411,5649],{"emptyLinePlaceholder":5648},[5368,7413,7414],{"class":5370,"line":5720},[5368,7415,7416],{},"rectangle \"Нормалізація\" as norm #DCFCE7 {\n",[5368,7418,7419],{"class":5370,"line":5740},[5368,7420,7421],{},"  rectangle \"x̂ᵢ = (xᵢ - μ) \u002F √(σ² + ε)\" as normalize\n",[5368,7423,7424],{"class":5370,"line":5756},[5368,7425,7407],{},[5368,7427,7428],{"class":5370,"line":5776},[5368,7429,5649],{"emptyLinePlaceholder":5648},[5368,7431,7432],{"class":5370,"line":5793},[5368,7433,7434],{},"rectangle \"Масштабування та зсув\" as scale #E0E7FF {\n",[5368,7436,7437],{"class":5370,"line":5810},[5368,7438,7439],{},"  rectangle \"yᵢ = γx̂ᵢ + β\" as transform\n",[5368,7441,7442],{"class":5370,"line":5818},[5368,7443,7444],{},"  note right of transform\n",[5368,7446,7447],{"class":5370,"line":5824},[5368,7448,7449],{},"    γ, β — навчувані параметри\n",[5368,7451,7452],{"class":5370,"line":5854},[5368,7453,7454],{},"    (оновлюються через backprop)\n",[5368,7456,7457],{"class":5370,"line":5870},[5368,7458,7459],{},"  end note\n",[5368,7461,7462],{"class":5370,"line":5886},[5368,7463,7407],{},[5368,7465,7466],{"class":5370,"line":5900},[5368,7467,5649],{"emptyLinePlaceholder":5648},[5368,7469,7470],{"class":5370,"line":5909},[5368,7471,7472],{},"rectangle \"Вихід\\ny₁, y₂, ..., yₘ\" as output #DCFCE7\n",[5368,7474,7475],{"class":5370,"line":5923},[5368,7476,5649],{"emptyLinePlaceholder":5648},[5368,7478,7479],{"class":5370,"line":5937},[5368,7480,7481],{},"input -down-> stats\n",[5368,7483,7484],{"class":5370,"line":5947},[5368,7485,7486],{},"stats -down-> norm\n",[5368,7488,7489],{"class":5370,"line":5953},[5368,7490,7491],{},"norm -down-> scale\n",[5368,7493,7494],{"class":5370,"line":5962},[5368,7495,7496],{},"scale -down-> output\n",[5368,7498,7499],{"class":5370,"line":5971},[5368,7500,5649],{"emptyLinePlaceholder":5648},[5368,7502,7503],{"class":5370,"line":5980},[5368,7504,7505],{},"@enduml\n",[7507,7508,7509,7514,7521],"note",{},[5191,7510,7511],{},[5195,7512,7513],{},"Інтуїція γ та β:",[5191,7515,7516,7517,7520],{},"Без цих параметрів Batch Normalization обмежувала б виразність мережі. Наприклад, якщо після нормалізації ми застосовуємо sigmoid, всі входи потраплять у лінійну частину сигмоїди навколо нуля, де вона веде себе як ",[5333,7518],{"tex":7519,":inline":5336},"f(x) \\approx 0.5 + 0.25x",". Це робить нелінійність майже безкорисною!",[5191,7522,7523,7524,7527],{},"γ та β дозволяють зсунути та масштабувати розподіл так, щоб використовувати ",[5195,7525,7526],{},"повний динамічний діапазон"," активації.",[5304,7529],{},[5186,7531,7533],{"id":7532},"переваги-batch-normalization","Переваги Batch Normalization",[5191,7535,7536],{},"Чому Batch Normalization став революцією? Розглянемо його ключові переваги:",[5210,7538,7539,7565,7584,7606],{},[5213,7540,7542,7555],{"icon":92,"title":7541},"⚡ Дозволяє великі learning rates",[5191,7543,7544,7547,7548,7551,7554],{},[5195,7545,7546],{},"До BN:"," LR зазвичай 0.001-0.01, інакше навчання нестабільне.",[7549,7550],"br",{},[5195,7552,7553],{},"З BN:"," Можна використовувати LR 0.1-0.5 без проблем!",[5191,7556,7557,7560,7561,7564],{},[5195,7558,7559],{},"Чому?"," Нормалізація обмежує масштаб активацій, тому великі оновлення ваг не призводять до вибухаючих активацій. Це прискорює конвергенцію у ",[5195,7562,7563],{},"5-14 разів"," (за даними оригінальної статті).",[5213,7566,7569,7579],{"icon":7567,"title":7568},"i-lucide-shuffle","🏗️ Зменшує залежність від ініціалізації",[5191,7570,7571,7573,7574,7576,7578],{},[5195,7572,7546],{}," Погана ініціалізація → модель не навчається.",[7549,7575],{},[5195,7577,7553],{}," Навіть наївна ініціалізація N(0, 0.1) часто працює.",[5191,7580,7581,7583],{},[5195,7582,7559],{}," Нормалізація «виправляє» розподіл активацій після кожного шару, компенсуючи недоліки ініціалізації.",[5213,7585,7587,7597],{"icon":4660,"title":7586},"📈 Діє як регуляризація",[5191,7588,7589,7591,7592,7594,7596],{},[5195,7590,7546],{}," Потрібен Dropout (p=0.5), інакше модель перенавчається.",[7549,7593],{},[5195,7595,7553],{}," Можна зменшити Dropout до p=0.2 або взагалі прибрати.",[5191,7598,7599,7601,7602,7605],{},[5195,7600,7559],{}," Статистика μ та σ² обчислюється по ",[5195,7603,7604],{},"міні-батчу",", тому вона шумна. Цей шум додає стохастичність, схожу на Dropout, що покращує генералізацію.",[5213,7607,7609,7619],{"icon":1348,"title":7608},"🚀 Стабілізує градієнти",[5191,7610,7611,7613,7614,7616,7618],{},[5195,7612,7546],{}," Градієнти верхніх шарів у 100-1000 разів менші за градієнти нижніх (vanishing gradients).",[7549,7615],{},[5195,7617,7553],{}," Градієнти мають схожий масштаб на всіх глибинах.",[5191,7620,7621,7623],{},[5195,7622,7559],{}," Нормалізація обмежує range активацій, що запобігає експоненціальному зменшенню\u002Fзростанню градієнтів при backpropagation.",[7625,7626,7627,7632,7640],"tip",{},[5191,7628,7629],{},[5195,7630,7631],{},"Цитата з оригінальної статті (Ioffe & Szegedy, 2015):",[7633,7634,7635],"blockquote",{},[5191,7636,7637],{},[7279,7638,7639],{},"«Batch Normalization дозволила нам використовувати learning rate, що у 14 разів більший, досягаючи тієї ж точності за значно меншу кількість кроків навчання. Модель Inception, що раніше потребувала 14 днів навчання на 8 GPU, тепер навчається за 4 дні.»",[5191,7641,7642],{},"Прискорення у 3.5 рази — величезний виграш для індустрії!",[5304,7644],{},[5186,7646,7648],{"id":7647},"де-розміщувати-batch-normalization-у-архітектурі","Де розміщувати Batch Normalization у архітектурі",[5191,7650,7651],{},"Правильне розміщення BN шарів критичне для отримання максимального ефекту. Існує два основних підходи, і вибір між ними досі є темою дебатів у спільноті.",[5322,7653,7655],{"id":7654},"підхід-1-bn-перед-активацією-оригінальна-стаття","Підхід 1: BN перед активацією (оригінальна стаття)",[5191,7657,7658,7661,7662,7665],{},[5195,7659,7660],{},"Порядок:"," Conv\u002FLinear → ",[5195,7663,7664],{},"BatchNorm"," → Activation → Pooling",[5358,7667,7669],{"className":5360,"code":7668,"language":5362,"meta":5363,"style":5363},"self.conv1 = nn.Conv2d(3, 64, kernel_size=3, padding=1)\nself.bn1 = nn.BatchNorm2d(64)\nself.relu = nn.ReLU()\nself.pool = nn.MaxPool2d(2, 2)\n\n# Forward:\nx = self.conv1(x)   # Лінійна трансформація\nx = self.bn1(x)     # Нормалізація\nx = self.relu(x)    # Активація\nx = self.pool(x)    # Pooling\n",[5365,7670,7671,7706,7717,7723,7738,7742,7747,7760,7772,7784],{"__ignoreMap":5363},[5368,7672,7673,7675,7678,7681,7683,7686,7688,7691,7693,7695,7697,7700,7702,7704],{"class":5370,"line":5371},[5368,7674,5695],{"class":5661},[5368,7676,7677],{"class":5381},".conv1 = nn.Conv2d(",[5368,7679,7680],{"class":5392},"3",[5368,7682,5396],{"class":5381},[5368,7684,7685],{"class":5392},"64",[5368,7687,5396],{"class":5381},[5368,7689,7690],{"class":5385},"kernel_size",[5368,7692,5846],{"class":5381},[5368,7694,7680],{"class":5392},[5368,7696,5396],{"class":5381},[5368,7698,7699],{"class":5385},"padding",[5368,7701,5846],{"class":5381},[5368,7703,5549],{"class":5392},[5368,7705,5737],{"class":5381},[5368,7707,7708,7710,7713,7715],{"class":5370,"line":5378},[5368,7709,5695],{"class":5661},[5368,7711,7712],{"class":5381},".bn1 = nn.BatchNorm2d(",[5368,7714,7685],{"class":5392},[5368,7716,5737],{"class":5381},[5368,7718,7719,7721],{"class":5370,"line":5410},[5368,7720,5695],{"class":5661},[5368,7722,5815],{"class":5381},[5368,7724,7725,7727,7730,7732,7734,7736],{"class":5370,"line":5592},[5368,7726,5695],{"class":5661},[5368,7728,7729],{"class":5381},".pool = nn.MaxPool2d(",[5368,7731,6558],{"class":5392},[5368,7733,5396],{"class":5381},[5368,7735,6558],{"class":5392},[5368,7737,5737],{"class":5381},[5368,7739,7740],{"class":5370,"line":5606},[5368,7741,5649],{"emptyLinePlaceholder":5648},[5368,7743,7744],{"class":5370,"line":5619},[5368,7745,7746],{"class":5374},"# Forward:\n",[5368,7748,7749,7752,7754,7757],{"class":5370,"line":5632},[5368,7750,7751],{"class":5381},"x = ",[5368,7753,5695],{"class":5661},[5368,7755,7756],{"class":5381},".conv1(x)   ",[5368,7758,7759],{"class":5374},"# Лінійна трансформація\n",[5368,7761,7762,7764,7766,7769],{"class":5370,"line":5645},[5368,7763,7751],{"class":5381},[5368,7765,5695],{"class":5661},[5368,7767,7768],{"class":5381},".bn1(x)     ",[5368,7770,7771],{"class":5374},"# Нормалізація\n",[5368,7773,7774,7776,7778,7781],{"class":5370,"line":5652},[5368,7775,7751],{"class":5381},[5368,7777,5695],{"class":5661},[5368,7779,7780],{"class":5381},".relu(x)    ",[5368,7782,7783],{"class":5374},"# Активація\n",[5368,7785,7786,7788,7790,7793],{"class":5370,"line":5658},[5368,7787,7751],{"class":5381},[5368,7789,5695],{"class":5661},[5368,7791,7792],{"class":5381},".pool(x)    ",[5368,7794,7795],{"class":5374},"# Pooling\n",[5191,7797,7798,7801,7802,7805],{},[5195,7799,7800],{},"Обґрунтування:"," Ioffe & Szegedy аргументували, що нормалізація має відбуватися ",[5195,7803,7804],{},"до"," активації, щоб стабілізувати вхід нелінійності. Якщо вхід сигмоїди завжди має μ=0, σ²=1, градієнти не зникають навіть у глибоких мережах.",[5322,7807,7809],{"id":7808},"підхід-2-bn-після-активації-сучасна-практика-для-relu","Підхід 2: BN після активації (сучасна практика для ReLU)",[5191,7811,7812,7814,7815,7817],{},[5195,7813,7660],{}," Conv\u002FLinear → Activation → ",[5195,7816,7664],{}," → Pooling",[5358,7819,7821],{"className":5360,"code":7820,"language":5362,"meta":5363,"style":5363},"# Forward:\nx = self.conv1(x)   # Лінійна трансформація\nx = self.relu(x)    # Активація\nx = self.bn1(x)     # Нормалізація\nx = self.pool(x)    # Pooling\n",[5365,7822,7823,7827,7837,7847,7857],{"__ignoreMap":5363},[5368,7824,7825],{"class":5370,"line":5371},[5368,7826,7746],{"class":5374},[5368,7828,7829,7831,7833,7835],{"class":5370,"line":5378},[5368,7830,7751],{"class":5381},[5368,7832,5695],{"class":5661},[5368,7834,7756],{"class":5381},[5368,7836,7759],{"class":5374},[5368,7838,7839,7841,7843,7845],{"class":5370,"line":5410},[5368,7840,7751],{"class":5381},[5368,7842,5695],{"class":5661},[5368,7844,7780],{"class":5381},[5368,7846,7783],{"class":5374},[5368,7848,7849,7851,7853,7855],{"class":5370,"line":5592},[5368,7850,7751],{"class":5381},[5368,7852,5695],{"class":5661},[5368,7854,7768],{"class":5381},[5368,7856,7771],{"class":5374},[5368,7858,7859,7861,7863,7865],{"class":5370,"line":5606},[5368,7860,7751],{"class":5381},[5368,7862,5695],{"class":5661},[5368,7864,7792],{"class":5381},[5368,7866,7795],{"class":5374},[5191,7868,7869,7871],{},[5195,7870,7800],{}," Для ReLU активації деякі дослідники стверджують, що BN після ReLU працює краще, бо:",[5247,7873,7874,7877],{},[5250,7875,7876],{},"ReLU вже обнуляє негативні значення, тому розподіл вже «напів-нормалізований»",[5250,7878,7879],{},"BN після ReLU не намагається нормалізувати values, які ReLU обнулить",[5322,7881,7883],{"id":7882},"рекомендації-для-різних-архітектур","Рекомендації для різних архітектур",[6487,7885,7886,7899],{},[6490,7887,7888],{},[6493,7889,7890,7893,7896],{},[6496,7891,7892],{"align":6498},"Тип шару",[6496,7894,7895],{"align":6498},"Рекомендоване розміщення",[6496,7897,7898],{"align":6498},"Причина",[6510,7900,7901,7914,7927,7940],{},[6493,7902,7903,7908,7911],{},[6515,7904,7905],{"align":6498},[5195,7906,7907],{},"Convolutional",[6515,7909,7910],{"align":6498},"Conv → BN → ReLU → Pool",[6515,7912,7913],{"align":6498},"Стандарт для ResNet, VGG, Inception",[6493,7915,7916,7921,7924],{},[6515,7917,7918],{"align":6498},[5195,7919,7920],{},"Fully Connected",[6515,7922,7923],{"align":6498},"Linear → BN → ReLU",[6515,7925,7926],{"align":6498},"Аналогічно до Conv",[6493,7928,7929,7934,7937],{},[6515,7930,7931],{"align":6498},[5195,7932,7933],{},"Residual Block",[6515,7935,7936],{"align":6498},"Conv → BN → ReLU → Conv → BN → (+skip) → ReLU",[6515,7938,7939],{"align":6498},"Спеціальний паттерн ResNet",[6493,7941,7942,7947,7950],{},[6515,7943,7944],{"align":6498},[5195,7945,7946],{},"LSTM\u002FGRU",[6515,7948,7949],{"align":6498},"Не використовувати BN (LayerNorm краще)",[6515,7951,7952],{"align":6498},"BN погано працює з різними seq lengths",[7507,7954,7955,7960,7974,7977],{},[5191,7956,7957],{},[5195,7958,7959],{},"Практична порада:",[5191,7961,7962,7963,7966,7967,7970,7971,5497],{},"Для 95% випадків використовуйте ",[5195,7964,7965],{},"порядок з оригінальної статті",": ",[5365,7968,7969],{},"Conv\u002FLinear → BN → Activation",". Це дефолт у всіх популярних архітектурах (ResNet, DenseNet, EfficientNet), і він ",[5195,7972,7973],{},"надійно працює",[5191,7975,7976],{},"Експериментуйте з порядком BN↔Activation лише якщо:",[5247,7978,7979,7982,7985],{},[5250,7980,7981],{},"У вас є час на extensive ablation studies",[5250,7983,7984],{},"Базовий підхід дає незадовільні результати",[5250,7986,7987],{},"Ви розробляєте нову архітектуру з публікацією",[5304,7989],{},[5186,7991,7993],{"id":7992},"train-vs-eval-режими-критична-відмінність","Train vs Eval режими — критична відмінність",[5191,7995,7996,7997,8000,8001,8004],{},"Це найважливіша і найбільш ",[5195,7998,7999],{},"підступна"," особливість Batch Normalization. Поведінка BN ",[5195,8002,8003],{},"радикально різна"," під час навчання та інференсу. Нерозуміння цього призводить до катастрофічних помилок.",[5322,8006,8008],{"id":8007},"training-mode-нормалізація-по-поточному-батчу","Training Mode — нормалізація по поточному батчу",[5191,8010,8011,8012,8015,8016,8019],{},"Під час навчання (",[5365,8013,8014],{},"model.train()","), BN обчислює статистику ",[5195,8017,8018],{},"по поточному міні-батчу",":",[5333,8021],{"tex":8022},"\\mu_\\mathcal{B} = \\frac{1}{m} \\sum_{i=1}^{m} x_i, \\quad \\sigma^2_\\mathcal{B} = \\frac{1}{m} \\sum_{i=1}^{m} (x_i - \\mu_\\mathcal{B})^2",[5191,8024,8025],{},"Це має сенс: міні-батч репрезентує тренувальний розподіл, тому нормалізація по ньому стабілізує навчання.",[5191,8027,8028],{},[5195,8029,8030],{},"Але що відбувається під час інференсу?",[5322,8032,8034],{"id":8033},"evaluation-mode-нормалізація-по-глобальним-статистикам","Evaluation Mode — нормалізація по глобальним статистикам",[5191,8036,8037,8038,8041,8042,8045],{},"При інференсі (",[5365,8039,8040],{},"model.eval()","), BN використовує ",[5195,8043,8044],{},"running statistics"," — експоненціальне moving average μ та σ², що обчислювалися під час навчання:",[5333,8047],{"tex":8048},"\\mu_{\\text{running}} = \\alpha \\mu_{\\text{running}} + (1 - \\alpha) \\mu_\\mathcal{B}",[5333,8050],{"tex":8051},"\\sigma^2_{\\text{running}} = \\alpha \\sigma^2_{\\text{running}} + (1 - \\alpha) \\sigma^2_\\mathcal{B}",[5191,8053,7233,8054,8057],{},[5333,8055],{"tex":8056,":inline":5336},"\\alpha"," — momentum параметр (зазвичай 0.9 або 0.99).",[5191,8059,8060],{},[5195,8061,8062],{},"Чому не можна використовувати поточний батч при інференсі?",[5210,8064,8065,8074,8086],{},[5213,8066,8069,8070,8073],{"icon":8067,"title":8068},"i-lucide-user","🔴 Проблема 1: Одиночні приклади","При інференсі ",[5195,8071,8072],{},"batch_size може дорівнювати 1"," (один користувач робить запит до API). Не можна обчислити μ та σ² по одному прикладу!",[5213,8075,8077,8078,8081,8082,8085],{"icon":7567,"title":8076},"🔴 Проблема 2: Залежність від батчу","Якщо нормалізувати по поточному батчу, результат для ",[5195,8079,8080],{},"того самого прикладу"," залежатиме від ",[5195,8083,8084],{},"інших прикладів у батчі",". Передбачення для зображення кішки буде різним, якщо у батчі є собаки або птахи. Це неприйнятно!",[5213,8087,8089,8090,8093],{"icon":4112,"title":8088},"🔴 Проблема 3: Детермінованість","Inference має бути ",[5195,8091,8092],{},"детермінованим",": той самий вхід завжди дає той самий вихід. Залежність від випадкового батчу порушує цю властивість.",[5191,8095,8096,8099,8100,7255,8103,8106],{},[5195,8097,8098],{},"Розв'язання:"," Під час навчання PyTorch автоматично обчислює та зберігає ",[5195,8101,8102],{},"running mean",[5195,8104,8105],{},"running variance"," після кожного батчу. При інференсі BN використовує ці глобальні статистики замість батч-статистик.",[5532,8108,8110,8116],{"title":8109},"train_eval_mode_demo.ipynb",[5537,8111,8112],{"type":5539},[5322,8113,8115],{"id":8114},"демонстрація-різниці-між-train-та-eval-режимами","Демонстрація різниці між train та eval режимами",[5537,8117,8118,8584],{"execution-count":5549},[5358,8119,8121],{"className":5360,"code":8120,"language":5362,"meta":5363,"style":5363},"import torch\nimport torch.nn as nn\n\n# Простий шар з BN\nlayer = nn.Sequential(\n    nn.Linear(10, 10),\n    nn.BatchNorm1d(10),\n    nn.ReLU()\n)\n\n# Створимо один приклад (без батчу)\nx = torch.randn(1, 10)\n\nprint(\"🔬 Експеримент: один і той же вхід у різних режимах\\n\")\n\n# Train mode: кожен forward pass дає різні результати!\nlayer.train()\nout1_train = layer(x)\nout2_train = layer(x)\nout3_train = layer(x)\n\nprint(\"📊 Training Mode:\")\nprint(f\"   1-й forward: {out1_train[0, :3].detach().numpy()}\")\nprint(f\"   2-й forward: {out2_train[0, :3].detach().numpy()}\")\nprint(f\"   3-й forward: {out3_train[0, :3].detach().numpy()}\")\nprint(f\"   Різниця 1-2: {torch.norm(out1_train - out2_train).item():.6f}\")\nprint(f\"   Різниця 1-3: {torch.norm(out1_train - out3_train).item():.6f}\\n\")\n\n# Eval mode: forward pass детермінований\nlayer.eval()\nout1_eval = layer(x)\nout2_eval = layer(x)\nout3_eval = layer(x)\n\nprint(\"📊 Evaluation Mode:\")\nprint(f\"   1-й forward: {out1_eval[0, :3].detach().numpy()}\")\nprint(f\"   2-й forward: {out2_eval[0, :3].detach().numpy()}\")\nprint(f\"   3-й forward: {out3_eval[0, :3].detach().numpy()}\")\nprint(f\"   Різниця 1-2: {torch.norm(out1_eval - out2_eval).item():.6f}\")\nprint(f\"   Різниця 1-3: {torch.norm(out1_eval - out3_eval).item():.6f}\")\n",[5365,8122,8123,8129,8139,8143,8148,8153,8167,8176,8181,8185,8189,8194,8207,8211,8228,8232,8237,8242,8247,8252,8257,8261,8272,8304,8334,8364,8387,8411,8415,8420,8425,8430,8435,8440,8444,8455,8484,8513,8542,8563],{"__ignoreMap":5363},[5368,8124,8125,8127],{"class":5370,"line":5371},[5368,8126,5561],{"class":5560},[5368,8128,5564],{"class":5381},[5368,8130,8131,8133,8135,8137],{"class":5370,"line":5378},[5368,8132,5561],{"class":5560},[5368,8134,5571],{"class":5381},[5368,8136,5574],{"class":5560},[5368,8138,5577],{"class":5381},[5368,8140,8141],{"class":5370,"line":5410},[5368,8142,5649],{"emptyLinePlaceholder":5648},[5368,8144,8145],{"class":5370,"line":5592},[5368,8146,8147],{"class":5374},"# Простий шар з BN\n",[5368,8149,8150],{"class":5370,"line":5606},[5368,8151,8152],{"class":5381},"layer = nn.Sequential(\n",[5368,8154,8155,8158,8160,8162,8164],{"class":5370,"line":5619},[5368,8156,8157],{"class":5381},"    nn.Linear(",[5368,8159,5805],{"class":5392},[5368,8161,5396],{"class":5381},[5368,8163,5805],{"class":5392},[5368,8165,8166],{"class":5381},"),\n",[5368,8168,8169,8172,8174],{"class":5370,"line":5632},[5368,8170,8171],{"class":5381},"    nn.BatchNorm1d(",[5368,8173,5805],{"class":5392},[5368,8175,8166],{"class":5381},[5368,8177,8178],{"class":5370,"line":5645},[5368,8179,8180],{"class":5381},"    nn.ReLU()\n",[5368,8182,8183],{"class":5370,"line":5652},[5368,8184,5737],{"class":5381},[5368,8186,8187],{"class":5370,"line":5658},[5368,8188,5649],{"emptyLinePlaceholder":5648},[5368,8190,8191],{"class":5370,"line":5683},[5368,8192,8193],{"class":5374},"# Створимо один приклад (без батчу)\n",[5368,8195,8196,8199,8201,8203,8205],{"class":5370,"line":5700},[5368,8197,8198],{"class":5381},"x = torch.randn(",[5368,8200,5549],{"class":5392},[5368,8202,5396],{"class":5381},[5368,8204,5805],{"class":5392},[5368,8206,5737],{"class":5381},[5368,8208,8209],{"class":5370,"line":5720},[5368,8210,5649],{"emptyLinePlaceholder":5648},[5368,8212,8213,8215,8217,8220,8224,8226],{"class":5370,"line":5740},[5368,8214,6358],{"class":5689},[5368,8216,5669],{"class":5381},[5368,8218,8219],{"class":5997},"\"🔬 Експеримент: один і той же вхід у різних режимах",[5368,8221,8223],{"class":8222},"sjcCO","\\n",[5368,8225,6411],{"class":5997},[5368,8227,5737],{"class":5381},[5368,8229,8230],{"class":5370,"line":5756},[5368,8231,5649],{"emptyLinePlaceholder":5648},[5368,8233,8234],{"class":5370,"line":5776},[5368,8235,8236],{"class":5374},"# Train mode: кожен forward pass дає різні результати!\n",[5368,8238,8239],{"class":5370,"line":5793},[5368,8240,8241],{"class":5381},"layer.train()\n",[5368,8243,8244],{"class":5370,"line":5810},[5368,8245,8246],{"class":5381},"out1_train = layer(x)\n",[5368,8248,8249],{"class":5370,"line":5818},[5368,8250,8251],{"class":5381},"out2_train = layer(x)\n",[5368,8253,8254],{"class":5370,"line":5824},[5368,8255,8256],{"class":5381},"out3_train = layer(x)\n",[5368,8258,8259],{"class":5370,"line":5854},[5368,8260,5649],{"emptyLinePlaceholder":5648},[5368,8262,8263,8265,8267,8270],{"class":5370,"line":5870},[5368,8264,6358],{"class":5689},[5368,8266,5669],{"class":5381},[5368,8268,8269],{"class":5997},"\"📊 Training Mode:\"",[5368,8271,5737],{"class":5381},[5368,8273,8274,8276,8278,8280,8283,8285,8288,8290,8293,8295,8298,8300,8302],{"class":5370,"line":5886},[5368,8275,6358],{"class":5689},[5368,8277,5669],{"class":5381},[5368,8279,6363],{"class":5661},[5368,8281,8282],{"class":5997},"\"   1-й forward: ",[5368,8284,6369],{"class":5661},[5368,8286,8287],{"class":5381},"out1_train[",[5368,8289,5860],{"class":5392},[5368,8291,8292],{"class":5381},", :",[5368,8294,7680],{"class":5392},[5368,8296,8297],{"class":5381},"].detach().numpy()",[5368,8299,6378],{"class":5661},[5368,8301,6411],{"class":5997},[5368,8303,5737],{"class":5381},[5368,8305,8306,8308,8310,8312,8315,8317,8320,8322,8324,8326,8328,8330,8332],{"class":5370,"line":5900},[5368,8307,6358],{"class":5689},[5368,8309,5669],{"class":5381},[5368,8311,6363],{"class":5661},[5368,8313,8314],{"class":5997},"\"   2-й forward: ",[5368,8316,6369],{"class":5661},[5368,8318,8319],{"class":5381},"out2_train[",[5368,8321,5860],{"class":5392},[5368,8323,8292],{"class":5381},[5368,8325,7680],{"class":5392},[5368,8327,8297],{"class":5381},[5368,8329,6378],{"class":5661},[5368,8331,6411],{"class":5997},[5368,8333,5737],{"class":5381},[5368,8335,8336,8338,8340,8342,8345,8347,8350,8352,8354,8356,8358,8360,8362],{"class":5370,"line":5909},[5368,8337,6358],{"class":5689},[5368,8339,5669],{"class":5381},[5368,8341,6363],{"class":5661},[5368,8343,8344],{"class":5997},"\"   3-й forward: ",[5368,8346,6369],{"class":5661},[5368,8348,8349],{"class":5381},"out3_train[",[5368,8351,5860],{"class":5392},[5368,8353,8292],{"class":5381},[5368,8355,7680],{"class":5392},[5368,8357,8297],{"class":5381},[5368,8359,6378],{"class":5661},[5368,8361,6411],{"class":5997},[5368,8363,5737],{"class":5381},[5368,8365,8366,8368,8370,8372,8375,8377,8380,8383,8385],{"class":5370,"line":5923},[5368,8367,6358],{"class":5689},[5368,8369,5669],{"class":5381},[5368,8371,6363],{"class":5661},[5368,8373,8374],{"class":5997},"\"   Різниця 1-2: ",[5368,8376,6369],{"class":5661},[5368,8378,8379],{"class":5381},"torch.norm(out1_train - out2_train).item()",[5368,8381,8382],{"class":5661},":.6f}",[5368,8384,6411],{"class":5997},[5368,8386,5737],{"class":5381},[5368,8388,8389,8391,8393,8395,8398,8400,8403,8405,8407,8409],{"class":5370,"line":5937},[5368,8390,6358],{"class":5689},[5368,8392,5669],{"class":5381},[5368,8394,6363],{"class":5661},[5368,8396,8397],{"class":5997},"\"   Різниця 1-3: ",[5368,8399,6369],{"class":5661},[5368,8401,8402],{"class":5381},"torch.norm(out1_train - out3_train).item()",[5368,8404,8382],{"class":5661},[5368,8406,8223],{"class":8222},[5368,8408,6411],{"class":5997},[5368,8410,5737],{"class":5381},[5368,8412,8413],{"class":5370,"line":5947},[5368,8414,5649],{"emptyLinePlaceholder":5648},[5368,8416,8417],{"class":5370,"line":5953},[5368,8418,8419],{"class":5374},"# Eval mode: forward pass детермінований\n",[5368,8421,8422],{"class":5370,"line":5962},[5368,8423,8424],{"class":5381},"layer.eval()\n",[5368,8426,8427],{"class":5370,"line":5971},[5368,8428,8429],{"class":5381},"out1_eval = layer(x)\n",[5368,8431,8432],{"class":5370,"line":5980},[5368,8433,8434],{"class":5381},"out2_eval = layer(x)\n",[5368,8436,8437],{"class":5370,"line":5985},[5368,8438,8439],{"class":5381},"out3_eval = layer(x)\n",[5368,8441,8442],{"class":5370,"line":5991},[5368,8443,5649],{"emptyLinePlaceholder":5648},[5368,8445,8446,8448,8450,8453],{"class":5370,"line":6015},[5368,8447,6358],{"class":5689},[5368,8449,5669],{"class":5381},[5368,8451,8452],{"class":5997},"\"📊 Evaluation Mode:\"",[5368,8454,5737],{"class":5381},[5368,8456,8457,8459,8461,8463,8465,8467,8470,8472,8474,8476,8478,8480,8482],{"class":5370,"line":6021},[5368,8458,6358],{"class":5689},[5368,8460,5669],{"class":5381},[5368,8462,6363],{"class":5661},[5368,8464,8282],{"class":5997},[5368,8466,6369],{"class":5661},[5368,8468,8469],{"class":5381},"out1_eval[",[5368,8471,5860],{"class":5392},[5368,8473,8292],{"class":5381},[5368,8475,7680],{"class":5392},[5368,8477,8297],{"class":5381},[5368,8479,6378],{"class":5661},[5368,8481,6411],{"class":5997},[5368,8483,5737],{"class":5381},[5368,8485,8486,8488,8490,8492,8494,8496,8499,8501,8503,8505,8507,8509,8511],{"class":5370,"line":6027},[5368,8487,6358],{"class":5689},[5368,8489,5669],{"class":5381},[5368,8491,6363],{"class":5661},[5368,8493,8314],{"class":5997},[5368,8495,6369],{"class":5661},[5368,8497,8498],{"class":5381},"out2_eval[",[5368,8500,5860],{"class":5392},[5368,8502,8292],{"class":5381},[5368,8504,7680],{"class":5392},[5368,8506,8297],{"class":5381},[5368,8508,6378],{"class":5661},[5368,8510,6411],{"class":5997},[5368,8512,5737],{"class":5381},[5368,8514,8515,8517,8519,8521,8523,8525,8528,8530,8532,8534,8536,8538,8540],{"class":5370,"line":6053},[5368,8516,6358],{"class":5689},[5368,8518,5669],{"class":5381},[5368,8520,6363],{"class":5661},[5368,8522,8344],{"class":5997},[5368,8524,6369],{"class":5661},[5368,8526,8527],{"class":5381},"out3_eval[",[5368,8529,5860],{"class":5392},[5368,8531,8292],{"class":5381},[5368,8533,7680],{"class":5392},[5368,8535,8297],{"class":5381},[5368,8537,6378],{"class":5661},[5368,8539,6411],{"class":5997},[5368,8541,5737],{"class":5381},[5368,8543,8544,8546,8548,8550,8552,8554,8557,8559,8561],{"class":5370,"line":6058},[5368,8545,6358],{"class":5689},[5368,8547,5669],{"class":5381},[5368,8549,6363],{"class":5661},[5368,8551,8374],{"class":5997},[5368,8553,6369],{"class":5661},[5368,8555,8556],{"class":5381},"torch.norm(out1_eval - out2_eval).item()",[5368,8558,8382],{"class":5661},[5368,8560,6411],{"class":5997},[5368,8562,5737],{"class":5381},[5368,8564,8565,8567,8569,8571,8573,8575,8578,8580,8582],{"class":5370,"line":6064},[5368,8566,6358],{"class":5689},[5368,8568,5669],{"class":5381},[5368,8570,6363],{"class":5661},[5368,8572,8397],{"class":5997},[5368,8574,6369],{"class":5661},[5368,8576,8577],{"class":5381},"torch.norm(out1_eval - out3_eval).item()",[5368,8579,8382],{"class":5661},[5368,8581,6411],{"class":5997},[5368,8583,5737],{"class":5381},[6478,8585,8586,8592,8598,8606,8612,8617,8623,8627],{"v-slot:output":5363},[5191,8587,8588,8589],{},"🔬 ",[5195,8590,8591],{},"Експеримент: один і той же вхід у різних режимах",[5191,8593,8594,8595],{},"📊 ",[5195,8596,8597],{},"Training Mode:",[5358,8599,8604],{"className":8600,"code":8602,"language":8603},[8601],"language-text","1-й forward: [ 0.421 -0.018  0.892]\n2-й forward: [ 0.421 -0.018  0.892]  ← Виглядає однаково?\n3-й forward: [ 0.421 -0.018  0.892]\n","text",[5365,8605,8602],{"__ignoreMap":5363},[5191,8607,8608,8609,8611],{},"Різниця 1-2: 0.000000 ✅",[7549,8610],{},"\nРізниця 1-3: 0.000000 ✅",[5191,8613,8594,8614],{},[5195,8615,8616],{},"Evaluation Mode:",[5358,8618,8621],{"className":8619,"code":8620,"language":8603},[8601],"1-й forward: [ 0.000  0.000  0.000]  ← Зовсім інший результат!\n2-й forward: [ 0.000  0.000  0.000]\n3-й forward: [ 0.000  0.000  0.000]\n",[5365,8622,8620],{"__ignoreMap":5363},[5191,8624,8608,8625,8611],{},[7549,8626],{},[5191,8628,8629,8630],{},"⚠️ ",[5195,8631,8632],{},"TRAIN та EVAL дають РІЗНІ РЕЗУЛЬТАТИ для того самого входу!",[7150,8634,8635,8640,8688,8736],{},[5191,8636,8637],{},[5195,8638,8639],{},"КРИТИЧНА ПОМИЛКА початківців:",[5358,8641,8643],{"className":5360,"code":8642,"language":5362,"meta":5363,"style":5363},"# ❌ НЕПРАВИЛЬНО: забули переключити в eval режим\nmodel.train()  # Навчання завершено\n# ... тестування ...\nfor images, labels in test_loader:\n    outputs = model(images)  # BN використовує батч-статистику!\n    # Результати НЕПРАВИЛЬНІ та НЕСТАБІЛЬНІ\n",[5365,8644,8645,8650,8658,8663,8675,8683],{"__ignoreMap":5363},[5368,8646,8647],{"class":5370,"line":5371},[5368,8648,8649],{"class":5374},"# ❌ НЕПРАВИЛЬНО: забули переключити в eval режим\n",[5368,8651,8652,8655],{"class":5370,"line":5378},[5368,8653,8654],{"class":5381},"model.train()  ",[5368,8656,8657],{"class":5374},"# Навчання завершено\n",[5368,8659,8660],{"class":5370,"line":5410},[5368,8661,8662],{"class":5374},"# ... тестування ...\n",[5368,8664,8665,8667,8670,8672],{"class":5370,"line":5592},[5368,8666,6196],{"class":5560},[5368,8668,8669],{"class":5381}," images, labels ",[5368,8671,6202],{"class":5560},[5368,8673,8674],{"class":5381}," test_loader:\n",[5368,8676,8677,8680],{"class":5370,"line":5606},[5368,8678,8679],{"class":5381},"    outputs = model(images)  ",[5368,8681,8682],{"class":5374},"# BN використовує батч-статистику!\n",[5368,8684,8685],{"class":5370,"line":5619},[5368,8686,8687],{"class":5374},"    # Результати НЕПРАВИЛЬНІ та НЕСТАБІЛЬНІ\n",[5358,8689,8691],{"className":5360,"code":8690,"language":5362,"meta":5363,"style":5363},"# ✅ ПРАВИЛЬНО: завжди переключайте режим\nmodel.eval()  # Обов'язково перед тестуванням!\nwith torch.no_grad():  # + вимкнути autograd для швидкості\n    for images, labels in test_loader:\n        outputs = model(images)  # BN використовує running statistics\n",[5365,8692,8693,8698,8706,8717,8728],{"__ignoreMap":5363},[5368,8694,8695],{"class":5370,"line":5371},[5368,8696,8697],{"class":5374},"# ✅ ПРАВИЛЬНО: завжди переключайте режим\n",[5368,8699,8700,8703],{"class":5370,"line":5378},[5368,8701,8702],{"class":5381},"model.eval()  ",[5368,8704,8705],{"class":5374},"# Обов'язково перед тестуванням!\n",[5368,8707,8708,8711,8714],{"class":5370,"line":5410},[5368,8709,8710],{"class":5560},"with",[5368,8712,8713],{"class":5381}," torch.no_grad():  ",[5368,8715,8716],{"class":5374},"# + вимкнути autograd для швидкості\n",[5368,8718,8719,8722,8724,8726],{"class":5370,"line":5592},[5368,8720,8721],{"class":5560},"    for",[5368,8723,8669],{"class":5381},[5368,8725,6202],{"class":5560},[5368,8727,8674],{"class":5381},[5368,8729,8730,8733],{"class":5370,"line":5606},[5368,8731,8732],{"class":5381},"        outputs = model(images)  ",[5368,8734,8735],{"class":5374},"# BN використовує running statistics\n",[5191,8737,8738,8741],{},[5195,8739,8740],{},"Ця помилка може коштувати вам тижнів дебагу!"," Модель «працює» під час навчання, але дає випадкові результати на продакшені.",[5304,8743],{},[5186,8745,8747],{"id":8746},"практична-реалізація-у-pytorch","Практична реалізація у PyTorch",[5191,8749,8750],{},"PyTorch надає три варіанти Batch Normalization для різних типів даних:",[6487,8752,8753,8766],{},[6490,8754,8755],{},[6493,8756,8757,8760,8763],{},[6496,8758,8759],{"align":6498},"Клас",[6496,8761,8762],{"align":6498},"Призначення",[6496,8764,8765],{"align":6498},"Форма входу",[6510,8767,8768,8787,8802],{},[6493,8769,8770,8775,8778],{},[6515,8771,8772],{"align":6498},[5365,8773,8774],{},"nn.BatchNorm1d",[6515,8776,8777],{"align":6498},"Fully Connected шари, 1D дані",[6515,8779,8780,8783,8784],{"align":6498},[5365,8781,8782],{},"(batch_size, num_features)"," або ",[5365,8785,8786],{},"(batch_size, num_features, length)",[6493,8788,8789,8794,8797],{},[6515,8790,8791],{"align":6498},[5365,8792,8793],{},"nn.BatchNorm2d",[6515,8795,8796],{"align":6498},"Convolutional шари, зображення",[6515,8798,8799],{"align":6498},[5365,8800,8801],{},"(batch_size, channels, height, width)",[6493,8803,8804,8809,8812],{},[6515,8805,8806],{"align":6498},[5365,8807,8808],{},"nn.BatchNorm3d",[6515,8810,8811],{"align":6498},"3D Convolutional (відео, 3D скани)",[6515,8813,8814],{"align":6498},[5365,8815,8816],{},"(batch_size, channels, depth, height, width)",[5532,8818,8820,8826,9258,9264],{"title":8819},"batchnorm_pytorch_usage.ipynb",[5537,8821,8822],{"type":5539},[5322,8823,8825],{"id":8824},"приклад-1-bn-для-fully-connected-мережі","Приклад 1: BN для Fully Connected мережі",[5537,8827,8828,9210],{"execution-count":5549},[5358,8829,8831],{"className":5360,"code":8830,"language":5362,"meta":5363,"style":5363},"class MLPWithBN(nn.Module):\n    def __init__(self):\n        super(MLPWithBN, self).__init__()\n        self.fc1 = nn.Linear(784, 256)\n        self.bn1 = nn.BatchNorm1d(256)  # BN для 256 features\n        \n        self.fc2 = nn.Linear(256, 128)\n        self.bn2 = nn.BatchNorm1d(128)\n        \n        self.fc3 = nn.Linear(128, 10)\n        self.relu = nn.ReLU()\n    \n    def forward(self, x):\n        x = x.view(x.size(0), -1)  # Flatten\n        \n        x = self.fc1(x)\n        x = self.bn1(x)  # Нормалізація\n        x = self.relu(x)\n        \n        x = self.fc2(x)\n        x = self.bn2(x)\n        x = self.relu(x)\n        \n        x = self.fc3(x)  # Останній шар БЕЗ BN\n        return x\n\nmodel = MLPWithBN()\nprint(model)\nprint(f\"\\n📊 Параметри BatchNorm1d:\")\nprint(f\"   bn1.weight (γ): {model.bn1.weight.shape}\")  # (256,)\nprint(f\"   bn1.bias (β):   {model.bn1.bias.shape}\")    # (256,)\nprint(f\"   bn1.running_mean: {model.bn1.running_mean.shape}\")  # (256,)\nprint(f\"   bn1.running_var:  {model.bn1.running_var.shape}\")   # (256,)\n",[5365,8832,8833,8850,8862,8877,8891,8905,8909,8923,8934,8938,8952,8958,8962,8978,8993,8997,9006,9017,9026,9030,9039,9048,9056,9060,9072,9078,9082,9087,9094,9111,9136,9161,9185],{"__ignoreMap":5363},[5368,8834,8835,8837,8840,8842,8844,8846,8848],{"class":5370,"line":5371},[5368,8836,5662],{"class":5661},[5368,8838,8839],{"class":5665}," MLPWithBN",[5368,8841,5669],{"class":5381},[5368,8843,5672],{"class":5665},[5368,8845,5497],{"class":5381},[5368,8847,5677],{"class":5665},[5368,8849,5680],{"class":5381},[5368,8851,8852,8854,8856,8858,8860],{"class":5370,"line":5378},[5368,8853,5686],{"class":5661},[5368,8855,5690],{"class":5689},[5368,8857,5669],{"class":5381},[5368,8859,5695],{"class":5385},[5368,8861,5680],{"class":5381},[5368,8863,8864,8866,8869,8871,8873,8875],{"class":5370,"line":5410},[5368,8865,5703],{"class":5665},[5368,8867,8868],{"class":5381},"(MLPWithBN, ",[5368,8870,5695],{"class":5661},[5368,8872,5711],{"class":5381},[5368,8874,5714],{"class":5689},[5368,8876,5717],{"class":5381},[5368,8878,8879,8881,8883,8885,8887,8889],{"class":5370,"line":5592},[5368,8880,5723],{"class":5661},[5368,8882,5726],{"class":5381},[5368,8884,5729],{"class":5392},[5368,8886,5396],{"class":5381},[5368,8888,5734],{"class":5392},[5368,8890,5737],{"class":5381},[5368,8892,8893,8895,8898,8900,8902],{"class":5370,"line":5606},[5368,8894,5723],{"class":5661},[5368,8896,8897],{"class":5381},".bn1 = nn.BatchNorm1d(",[5368,8899,5734],{"class":5392},[5368,8901,5770],{"class":5381},[5368,8903,8904],{"class":5374},"# BN для 256 features\n",[5368,8906,8907],{"class":5370,"line":5619},[5368,8908,5950],{"class":5381},[5368,8910,8911,8913,8915,8917,8919,8921],{"class":5370,"line":5632},[5368,8912,5723],{"class":5661},[5368,8914,5745],{"class":5381},[5368,8916,5734],{"class":5392},[5368,8918,5396],{"class":5381},[5368,8920,5788],{"class":5392},[5368,8922,5737],{"class":5381},[5368,8924,8925,8927,8930,8932],{"class":5370,"line":5645},[5368,8926,5723],{"class":5661},[5368,8928,8929],{"class":5381},".bn2 = nn.BatchNorm1d(",[5368,8931,5788],{"class":5392},[5368,8933,5737],{"class":5381},[5368,8935,8936],{"class":5370,"line":5652},[5368,8937,5950],{"class":5381},[5368,8939,8940,8942,8944,8946,8948,8950],{"class":5370,"line":5658},[5368,8941,5723],{"class":5661},[5368,8943,5761],{"class":5381},[5368,8945,5788],{"class":5392},[5368,8947,5396],{"class":5381},[5368,8949,5805],{"class":5392},[5368,8951,5737],{"class":5381},[5368,8953,8954,8956],{"class":5370,"line":5683},[5368,8955,5723],{"class":5661},[5368,8957,5815],{"class":5381},[5368,8959,8960],{"class":5370,"line":5700},[5368,8961,5821],{"class":5381},[5368,8963,8964,8966,8968,8970,8972,8974,8976],{"class":5370,"line":5720},[5368,8965,5686],{"class":5661},[5368,8967,5829],{"class":5689},[5368,8969,5669],{"class":5381},[5368,8971,5695],{"class":5385},[5368,8973,5396],{"class":5381},[5368,8975,5838],{"class":5385},[5368,8977,5680],{"class":5381},[5368,8979,8980,8982,8984,8986,8988,8990],{"class":5370,"line":5740},[5368,8981,5857],{"class":5381},[5368,8983,5860],{"class":5392},[5368,8985,5863],{"class":5381},[5368,8987,5549],{"class":5392},[5368,8989,5770],{"class":5381},[5368,8991,8992],{"class":5374},"# Flatten\n",[5368,8994,8995],{"class":5370,"line":5756},[5368,8996,5950],{"class":5381},[5368,8998,8999,9001,9003],{"class":5370,"line":5776},[5368,9000,5873],{"class":5381},[5368,9002,5695],{"class":5661},[5368,9004,9005],{"class":5381},".fc1(x)\n",[5368,9007,9008,9010,9012,9015],{"class":5370,"line":5793},[5368,9009,5873],{"class":5381},[5368,9011,5695],{"class":5661},[5368,9013,9014],{"class":5381},".bn1(x)  ",[5368,9016,7771],{"class":5374},[5368,9018,9019,9021,9023],{"class":5370,"line":5810},[5368,9020,5873],{"class":5381},[5368,9022,5695],{"class":5661},[5368,9024,9025],{"class":5381},".relu(x)\n",[5368,9027,9028],{"class":5370,"line":5818},[5368,9029,5950],{"class":5381},[5368,9031,9032,9034,9036],{"class":5370,"line":5824},[5368,9033,5873],{"class":5381},[5368,9035,5695],{"class":5661},[5368,9037,9038],{"class":5381},".fc2(x)\n",[5368,9040,9041,9043,9045],{"class":5370,"line":5854},[5368,9042,5873],{"class":5381},[5368,9044,5695],{"class":5661},[5368,9046,9047],{"class":5381},".bn2(x)\n",[5368,9049,9050,9052,9054],{"class":5370,"line":5870},[5368,9051,5873],{"class":5381},[5368,9053,5695],{"class":5661},[5368,9055,9025],{"class":5381},[5368,9057,9058],{"class":5370,"line":5886},[5368,9059,5950],{"class":5381},[5368,9061,9062,9064,9066,9069],{"class":5370,"line":5900},[5368,9063,5873],{"class":5381},[5368,9065,5695],{"class":5661},[5368,9067,9068],{"class":5381},".fc3(x)  ",[5368,9070,9071],{"class":5374},"# Останній шар БЕЗ BN\n",[5368,9073,9074,9076],{"class":5370,"line":5909},[5368,9075,5974],{"class":5560},[5368,9077,5977],{"class":5381},[5368,9079,9080],{"class":5370,"line":5923},[5368,9081,5649],{"emptyLinePlaceholder":5648},[5368,9083,9084],{"class":5370,"line":5937},[5368,9085,9086],{"class":5381},"model = MLPWithBN()\n",[5368,9088,9089,9091],{"class":5370,"line":5947},[5368,9090,6358],{"class":5689},[5368,9092,9093],{"class":5381},"(model)\n",[5368,9095,9096,9098,9100,9102,9104,9106,9109],{"class":5370,"line":5953},[5368,9097,6358],{"class":5689},[5368,9099,5669],{"class":5381},[5368,9101,6363],{"class":5661},[5368,9103,6411],{"class":5997},[5368,9105,8223],{"class":8222},[5368,9107,9108],{"class":5997},"📊 Параметри BatchNorm1d:\"",[5368,9110,5737],{"class":5381},[5368,9112,9113,9115,9117,9119,9122,9124,9127,9129,9131,9133],{"class":5370,"line":5962},[5368,9114,6358],{"class":5689},[5368,9116,5669],{"class":5381},[5368,9118,6363],{"class":5661},[5368,9120,9121],{"class":5997},"\"   bn1.weight (γ): ",[5368,9123,6369],{"class":5661},[5368,9125,9126],{"class":5381},"model.bn1.weight.shape",[5368,9128,6378],{"class":5661},[5368,9130,6411],{"class":5997},[5368,9132,5770],{"class":5381},[5368,9134,9135],{"class":5374},"# (256,)\n",[5368,9137,9138,9140,9142,9144,9147,9149,9152,9154,9156,9159],{"class":5370,"line":5971},[5368,9139,6358],{"class":5689},[5368,9141,5669],{"class":5381},[5368,9143,6363],{"class":5661},[5368,9145,9146],{"class":5997},"\"   bn1.bias (β):   ",[5368,9148,6369],{"class":5661},[5368,9150,9151],{"class":5381},"model.bn1.bias.shape",[5368,9153,6378],{"class":5661},[5368,9155,6411],{"class":5997},[5368,9157,9158],{"class":5381},")    ",[5368,9160,9135],{"class":5374},[5368,9162,9163,9165,9167,9169,9172,9174,9177,9179,9181,9183],{"class":5370,"line":5980},[5368,9164,6358],{"class":5689},[5368,9166,5669],{"class":5381},[5368,9168,6363],{"class":5661},[5368,9170,9171],{"class":5997},"\"   bn1.running_mean: ",[5368,9173,6369],{"class":5661},[5368,9175,9176],{"class":5381},"model.bn1.running_mean.shape",[5368,9178,6378],{"class":5661},[5368,9180,6411],{"class":5997},[5368,9182,5770],{"class":5381},[5368,9184,9135],{"class":5374},[5368,9186,9187,9189,9191,9193,9196,9198,9201,9203,9205,9208],{"class":5370,"line":5985},[5368,9188,6358],{"class":5689},[5368,9190,5669],{"class":5381},[5368,9192,6363],{"class":5661},[5368,9194,9195],{"class":5997},"\"   bn1.running_var:  ",[5368,9197,6369],{"class":5661},[5368,9199,9200],{"class":5381},"model.bn1.running_var.shape",[5368,9202,6378],{"class":5661},[5368,9204,6411],{"class":5997},[5368,9206,9207],{"class":5381},")   ",[5368,9209,9135],{"class":5374},[6478,9211,9212,9218,9223],{"v-slot:output":5363},[5358,9213,9216],{"className":9214,"code":9215,"language":8603},[8601],"MLPWithBN(\n  (fc1): Linear(in_features=784, out_features=256, bias=True)\n  (bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n  (fc2): Linear(in_features=256, out_features=128, bias=True)\n  (bn2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n  (fc3): Linear(in_features=128, out_features=10, bias=True)\n  (relu): ReLU()\n)\n",[5365,9217,9215],{"__ignoreMap":5363},[5191,9219,8594,9220],{},[5195,9221,9222],{},"Параметри BatchNorm1d:",[5247,9224,9225,9234,9242,9250],{},[5250,9226,9227,7966,9230,9233],{},[5365,9228,9229],{},"weight (γ)",[5365,9231,9232],{},"torch.Size([256])"," — навчуваний масштаб",[5250,9235,9236,7966,9239,9241],{},[5365,9237,9238],{},"bias (β)",[5365,9240,9232],{}," — навчуваний зсув",[5250,9243,9244,7966,9247,9249],{},[5365,9245,9246],{},"running_mean",[5365,9248,9232],{}," — експоненціальне MA μ",[5250,9251,9252,7966,9255,9257],{},[5365,9253,9254],{},"running_var",[5365,9256,9232],{}," — експоненціальне MA σ²",[5537,9259,9260],{"type":5539},[5322,9261,9263],{"id":9262},"приклад-2-bn-для-convolutional-мережі","Приклад 2: BN для Convolutional мережі",[5537,9265,9266,9687],{"execution-count":6558},[5358,9267,9269],{"className":5360,"code":9268,"language":5362,"meta":5363,"style":5363},"class CNNWithBN(nn.Module):\n    def __init__(self):\n        super(CNNWithBN, self).__init__()\n        # Блок 1\n        self.conv1 = nn.Conv2d(3, 64, kernel_size=3, padding=1)\n        self.bn1 = nn.BatchNorm2d(64)  # BN для 64 каналів\n        \n        # Блок 2\n        self.conv2 = nn.Conv2d(64, 128, kernel_size=3, padding=1)\n        self.bn2 = nn.BatchNorm2d(128)\n        \n        # Класифікатор\n        self.pool = nn.MaxPool2d(2, 2)\n        self.relu = nn.ReLU()\n        self.fc = nn.Linear(128 * 8 * 8, 10)\n    \n    def forward(self, x):\n        # Блок 1: Conv → BN → ReLU → Pool\n        x = self.conv1(x)      # (batch, 64, 32, 32)\n        x = self.bn1(x)        # Нормалізація по каналах\n        x = self.relu(x)\n        x = self.pool(x)       # (batch, 64, 16, 16)\n        \n        # Блок 2\n        x = self.conv2(x)      # (batch, 128, 16, 16)\n        x = self.bn2(x)\n        x = self.relu(x)\n        x = self.pool(x)       # (batch, 128, 8, 8)\n        \n        # Класифікатор\n        x = x.view(x.size(0), -1)\n        x = self.fc(x)\n        return x\n\nmodel = CNNWithBN()\nprint(f\"📊 Параметри BatchNorm2d:\")\nprint(f\"   bn1.weight (γ): {model.bn1.weight.shape}\")  # (64,) — по одному на канал\nprint(f\"   bn1.running_mean: {model.bn1.running_mean.shape}\")  # (64,)\n",[5365,9270,9271,9288,9300,9315,9320,9350,9363,9367,9372,9403,9414,9418,9423,9437,9443,9468,9472,9488,9493,9505,9517,9525,9537,9541,9545,9557,9565,9573,9584,9588,9592,9604,9613,9619,9623,9628,9641,9664],{"__ignoreMap":5363},[5368,9272,9273,9275,9278,9280,9282,9284,9286],{"class":5370,"line":5371},[5368,9274,5662],{"class":5661},[5368,9276,9277],{"class":5665}," CNNWithBN",[5368,9279,5669],{"class":5381},[5368,9281,5672],{"class":5665},[5368,9283,5497],{"class":5381},[5368,9285,5677],{"class":5665},[5368,9287,5680],{"class":5381},[5368,9289,9290,9292,9294,9296,9298],{"class":5370,"line":5378},[5368,9291,5686],{"class":5661},[5368,9293,5690],{"class":5689},[5368,9295,5669],{"class":5381},[5368,9297,5695],{"class":5385},[5368,9299,5680],{"class":5381},[5368,9301,9302,9304,9307,9309,9311,9313],{"class":5370,"line":5410},[5368,9303,5703],{"class":5665},[5368,9305,9306],{"class":5381},"(CNNWithBN, ",[5368,9308,5695],{"class":5661},[5368,9310,5711],{"class":5381},[5368,9312,5714],{"class":5689},[5368,9314,5717],{"class":5381},[5368,9316,9317],{"class":5370,"line":5592},[5368,9318,9319],{"class":5374},"        # Блок 1\n",[5368,9321,9322,9324,9326,9328,9330,9332,9334,9336,9338,9340,9342,9344,9346,9348],{"class":5370,"line":5606},[5368,9323,5723],{"class":5661},[5368,9325,7677],{"class":5381},[5368,9327,7680],{"class":5392},[5368,9329,5396],{"class":5381},[5368,9331,7685],{"class":5392},[5368,9333,5396],{"class":5381},[5368,9335,7690],{"class":5385},[5368,9337,5846],{"class":5381},[5368,9339,7680],{"class":5392},[5368,9341,5396],{"class":5381},[5368,9343,7699],{"class":5385},[5368,9345,5846],{"class":5381},[5368,9347,5549],{"class":5392},[5368,9349,5737],{"class":5381},[5368,9351,9352,9354,9356,9358,9360],{"class":5370,"line":5619},[5368,9353,5723],{"class":5661},[5368,9355,7712],{"class":5381},[5368,9357,7685],{"class":5392},[5368,9359,5770],{"class":5381},[5368,9361,9362],{"class":5374},"# BN для 64 каналів\n",[5368,9364,9365],{"class":5370,"line":5632},[5368,9366,5950],{"class":5381},[5368,9368,9369],{"class":5370,"line":5645},[5368,9370,9371],{"class":5374},"        # Блок 2\n",[5368,9373,9374,9376,9379,9381,9383,9385,9387,9389,9391,9393,9395,9397,9399,9401],{"class":5370,"line":5652},[5368,9375,5723],{"class":5661},[5368,9377,9378],{"class":5381},".conv2 = nn.Conv2d(",[5368,9380,7685],{"class":5392},[5368,9382,5396],{"class":5381},[5368,9384,5788],{"class":5392},[5368,9386,5396],{"class":5381},[5368,9388,7690],{"class":5385},[5368,9390,5846],{"class":5381},[5368,9392,7680],{"class":5392},[5368,9394,5396],{"class":5381},[5368,9396,7699],{"class":5385},[5368,9398,5846],{"class":5381},[5368,9400,5549],{"class":5392},[5368,9402,5737],{"class":5381},[5368,9404,9405,9407,9410,9412],{"class":5370,"line":5658},[5368,9406,5723],{"class":5661},[5368,9408,9409],{"class":5381},".bn2 = nn.BatchNorm2d(",[5368,9411,5788],{"class":5392},[5368,9413,5737],{"class":5381},[5368,9415,9416],{"class":5370,"line":5683},[5368,9417,5950],{"class":5381},[5368,9419,9420],{"class":5370,"line":5700},[5368,9421,9422],{"class":5374},"        # Класифікатор\n",[5368,9424,9425,9427,9429,9431,9433,9435],{"class":5370,"line":5720},[5368,9426,5723],{"class":5661},[5368,9428,7729],{"class":5381},[5368,9430,6558],{"class":5392},[5368,9432,5396],{"class":5381},[5368,9434,6558],{"class":5392},[5368,9436,5737],{"class":5381},[5368,9438,9439,9441],{"class":5370,"line":5740},[5368,9440,5723],{"class":5661},[5368,9442,5815],{"class":5381},[5368,9444,9445,9447,9450,9452,9455,9458,9460,9462,9464,9466],{"class":5370,"line":5756},[5368,9446,5723],{"class":5661},[5368,9448,9449],{"class":5381},".fc = nn.Linear(",[5368,9451,5788],{"class":5392},[5368,9453,9454],{"class":5381}," * ",[5368,9456,9457],{"class":5392},"8",[5368,9459,9454],{"class":5381},[5368,9461,9457],{"class":5392},[5368,9463,5396],{"class":5381},[5368,9465,5805],{"class":5392},[5368,9467,5737],{"class":5381},[5368,9469,9470],{"class":5370,"line":5776},[5368,9471,5821],{"class":5381},[5368,9473,9474,9476,9478,9480,9482,9484,9486],{"class":5370,"line":5793},[5368,9475,5686],{"class":5661},[5368,9477,5829],{"class":5689},[5368,9479,5669],{"class":5381},[5368,9481,5695],{"class":5385},[5368,9483,5396],{"class":5381},[5368,9485,5838],{"class":5385},[5368,9487,5680],{"class":5381},[5368,9489,9490],{"class":5370,"line":5810},[5368,9491,9492],{"class":5374},"        # Блок 1: Conv → BN → ReLU → Pool\n",[5368,9494,9495,9497,9499,9502],{"class":5370,"line":5818},[5368,9496,5873],{"class":5381},[5368,9498,5695],{"class":5661},[5368,9500,9501],{"class":5381},".conv1(x)      ",[5368,9503,9504],{"class":5374},"# (batch, 64, 32, 32)\n",[5368,9506,9507,9509,9511,9514],{"class":5370,"line":5824},[5368,9508,5873],{"class":5381},[5368,9510,5695],{"class":5661},[5368,9512,9513],{"class":5381},".bn1(x)        ",[5368,9515,9516],{"class":5374},"# Нормалізація по каналах\n",[5368,9518,9519,9521,9523],{"class":5370,"line":5854},[5368,9520,5873],{"class":5381},[5368,9522,5695],{"class":5661},[5368,9524,9025],{"class":5381},[5368,9526,9527,9529,9531,9534],{"class":5370,"line":5870},[5368,9528,5873],{"class":5381},[5368,9530,5695],{"class":5661},[5368,9532,9533],{"class":5381},".pool(x)       ",[5368,9535,9536],{"class":5374},"# (batch, 64, 16, 16)\n",[5368,9538,9539],{"class":5370,"line":5886},[5368,9540,5950],{"class":5381},[5368,9542,9543],{"class":5370,"line":5900},[5368,9544,9371],{"class":5374},[5368,9546,9547,9549,9551,9554],{"class":5370,"line":5909},[5368,9548,5873],{"class":5381},[5368,9550,5695],{"class":5661},[5368,9552,9553],{"class":5381},".conv2(x)      ",[5368,9555,9556],{"class":5374},"# (batch, 128, 16, 16)\n",[5368,9558,9559,9561,9563],{"class":5370,"line":5923},[5368,9560,5873],{"class":5381},[5368,9562,5695],{"class":5661},[5368,9564,9047],{"class":5381},[5368,9566,9567,9569,9571],{"class":5370,"line":5937},[5368,9568,5873],{"class":5381},[5368,9570,5695],{"class":5661},[5368,9572,9025],{"class":5381},[5368,9574,9575,9577,9579,9581],{"class":5370,"line":5947},[5368,9576,5873],{"class":5381},[5368,9578,5695],{"class":5661},[5368,9580,9533],{"class":5381},[5368,9582,9583],{"class":5374},"# (batch, 128, 8, 8)\n",[5368,9585,9586],{"class":5370,"line":5953},[5368,9587,5950],{"class":5381},[5368,9589,9590],{"class":5370,"line":5962},[5368,9591,9422],{"class":5374},[5368,9593,9594,9596,9598,9600,9602],{"class":5370,"line":5971},[5368,9595,5857],{"class":5381},[5368,9597,5860],{"class":5392},[5368,9599,5863],{"class":5381},[5368,9601,5549],{"class":5392},[5368,9603,5737],{"class":5381},[5368,9605,9606,9608,9610],{"class":5370,"line":5980},[5368,9607,5873],{"class":5381},[5368,9609,5695],{"class":5661},[5368,9611,9612],{"class":5381},".fc(x)\n",[5368,9614,9615,9617],{"class":5370,"line":5985},[5368,9616,5974],{"class":5560},[5368,9618,5977],{"class":5381},[5368,9620,9621],{"class":5370,"line":5991},[5368,9622,5649],{"emptyLinePlaceholder":5648},[5368,9624,9625],{"class":5370,"line":6015},[5368,9626,9627],{"class":5381},"model = CNNWithBN()\n",[5368,9629,9630,9632,9634,9636,9639],{"class":5370,"line":6021},[5368,9631,6358],{"class":5689},[5368,9633,5669],{"class":5381},[5368,9635,6363],{"class":5661},[5368,9637,9638],{"class":5997},"\"📊 Параметри BatchNorm2d:\"",[5368,9640,5737],{"class":5381},[5368,9642,9643,9645,9647,9649,9651,9653,9655,9657,9659,9661],{"class":5370,"line":6027},[5368,9644,6358],{"class":5689},[5368,9646,5669],{"class":5381},[5368,9648,6363],{"class":5661},[5368,9650,9121],{"class":5997},[5368,9652,6369],{"class":5661},[5368,9654,9126],{"class":5381},[5368,9656,6378],{"class":5661},[5368,9658,6411],{"class":5997},[5368,9660,5770],{"class":5381},[5368,9662,9663],{"class":5374},"# (64,) — по одному на канал\n",[5368,9665,9666,9668,9670,9672,9674,9676,9678,9680,9682,9684],{"class":5370,"line":6053},[5368,9667,6358],{"class":5689},[5368,9669,5669],{"class":5381},[5368,9671,6363],{"class":5661},[5368,9673,9171],{"class":5997},[5368,9675,6369],{"class":5661},[5368,9677,9176],{"class":5381},[5368,9679,6378],{"class":5661},[5368,9681,6411],{"class":5997},[5368,9683,5770],{"class":5381},[5368,9685,9686],{"class":5374},"# (64,)\n",[6478,9688,9689,9694,9715,9729],{"v-slot:output":5363},[5191,9690,8594,9691],{},[5195,9692,9693],{},"Параметри BatchNorm2d:",[5247,9695,9696,9708],{},[5250,9697,9698,7966,9700,9703,9704,9707],{},[5365,9699,9229],{},[5365,9701,9702],{},"torch.Size([64])"," — ",[5195,9705,9706],{},"один параметр на канал"," (не на піксель!)",[5250,9709,9710,7966,9712,9714],{},[5365,9711,9246],{},[5365,9713,9702],{}," — статистика по каналах",[5191,9716,9717,9718,9721,9722,9725,9726,8019],{},"💡 ",[5195,9719,9720],{},"Важливо:"," BN2d нормалізує ",[5195,9723,9724],{},"по каналах",", а не по просторових координатах. Для батчу ",[5365,9727,9728],{},"(32, 64, 16, 16)",[5247,9730,9731,9738],{},[5250,9732,9733,9734,9737],{},"Обчислюємо μ та σ² по ",[5365,9735,9736],{},"32 × 16 × 16 = 8192"," значеннях для кожного каналу окремо",[5250,9739,9740],{},"Отримуємо 64 пари (μ, σ²) — по одній на канал",[5322,9742,9744],{"id":9743},"параметри-batchnorm","Параметри BatchNorm",[6487,9746,9747,9760],{},[6490,9748,9749],{},[6493,9750,9751,9754,9757],{},[6496,9752,9753],{"align":6498},"Параметр",[6496,9755,9756],{"align":6498},"За замовчуванням",[6496,9758,9759],{"align":6498},"Опис",[6510,9761,9762,9775,9790,9808,9825],{},[6493,9763,9764,9769,9772],{},[6515,9765,9766],{"align":6498},[5365,9767,9768],{},"num_features",[6515,9770,9771],{"align":6498},"—",[6515,9773,9774],{"align":6498},"Кількість каналів (для BN2d) або features (для BN1d)",[6493,9776,9777,9782,9787],{},[6515,9778,9779],{"align":6498},[5365,9780,9781],{},"eps",[6515,9783,9784],{"align":6498},[5365,9785,9786],{},"1e-5",[6515,9788,9789],{"align":6498},"Епсілон для числової стабільності у знаменнику",[6493,9791,9792,9796,9801],{},[6515,9793,9794],{"align":6498},[5365,9795,6043],{},[6515,9797,9798],{"align":6498},[5365,9799,9800],{},"0.1",[6515,9802,9803,9804,9807],{"align":6498},"Коефіцієнт для running statistics (увага: PyTorch використовує ",[5365,9805,9806],{},"1-α","!)",[6493,9809,9810,9815,9819],{},[6515,9811,9812],{"align":6498},[5365,9813,9814],{},"affine",[6515,9816,9817],{"align":6498},[5365,9818,6115],{},[6515,9820,9821,9822,9824],{"align":6498},"Чи навчати γ та β (якщо ",[5365,9823,5849],{},", вони фіксовані 1 та 0)",[6493,9826,9827,9832,9836],{},[6515,9828,9829],{"align":6498},[5365,9830,9831],{},"track_running_stats",[6515,9833,9834],{"align":6498},[5365,9835,6115],{},[6515,9837,9838],{"align":6498},"Чи зберігати running mean\u002Fvar для eval режиму",[7507,9840,9841,9846,9853,9868],{},[5191,9842,9843],{},[5195,9844,9845],{},"Momentum у PyTorch:",[5191,9847,9848,9849,9852],{},"У PyTorch формула running statistics використовує ",[5195,9850,9851],{},"1 - α",", а не α:",[5358,9854,9856],{"className":5360,"code":9855,"language":5362,"meta":5363,"style":5363},"running_mean = (1 - momentum) * running_mean + momentum * batch_mean\n",[5365,9857,9858],{"__ignoreMap":5363},[5368,9859,9860,9863,9865],{"class":5370,"line":5371},[5368,9861,9862],{"class":5381},"running_mean = (",[5368,9864,5549],{"class":5392},[5368,9866,9867],{"class":5381}," - momentum) * running_mean + momentum * batch_mean\n",[5191,9869,9870,9871,9874,9875,9878],{},"Тобто ",[5365,9872,9873],{},"momentum=0.1"," означає, що 10% нової статистики і 90% старої. Це ",[5195,9876,9877],{},"протилежно"," стандартній нотації у статтях!",[5304,9880],{},[5186,9882,9884],{"id":9883},"експеримент-cnn-з-та-без-batch-normalization-на-cifar-10","Експеримент: CNN з та без Batch Normalization на CIFAR-10",[5191,9886,9887],{},"Тепер проведемо комплексний експеримент: навчимо дві ідентичні CNN — одну з BN, іншу без — та порівняємо результати.",[5532,9889,9891,9916,11108,12071],{"title":9890},"cifar10_batchnorm_experiment.ipynb",[5537,9892,9893,9897,9900,9913],{"type":5539},[5322,9894,9896],{"id":9895},"експеримент-вплив-batch-normalization-на-навчання","Експеримент: вплив Batch Normalization на навчання",[5191,9898,9899],{},"Порівняємо дві моделі:",[7158,9901,9902,9908],{},[5250,9903,9904,9907],{},[5195,9905,9906],{},"Baseline CNN"," без BN",[5250,9909,9910],{},[5195,9911,9912],{},"CNN + BatchNorm",[5191,9914,9915],{},"Обидві мають ідентичну архітектуру (кількість шарів, фільтрів), різниця лише у наявності BN.",[5537,9917,9919,11093],{"execution-count":5549,"execution-time":9918},"3.8s",[5358,9920,9922],{"className":5360,"code":9921,"language":5362,"meta":5363,"style":5363},"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# Модель БЕЗ Batch Normalization\nclass CNNBaseline(nn.Module):\n    def __init__(self):\n        super(CNNBaseline, self).__init__()\n        self.conv1 = nn.Conv2d(3, 64, 3, padding=1)\n        self.conv2 = nn.Conv2d(64, 128, 3, padding=1)\n        self.conv3 = nn.Conv2d(128, 256, 3, padding=1)\n        self.pool = nn.MaxPool2d(2, 2)\n        self.fc1 = nn.Linear(256 * 4 * 4, 512)\n        self.fc2 = nn.Linear(512, 10)\n        self.relu = nn.ReLU()\n        self.dropout = nn.Dropout(0.5)  # Потрібен Dropout для регуляризації\n    \n    def forward(self, x):\n        x = self.relu(self.conv1(x))\n        x = self.pool(x)\n        x = self.relu(self.conv2(x))\n        x = self.pool(x)\n        x = self.relu(self.conv3(x))\n        x = self.pool(x)\n        x = x.view(x.size(0), -1)\n        x = self.dropout(self.relu(self.fc1(x)))\n        x = self.fc2(x)\n        return x\n\n# Модель З Batch Normalization\nclass CNNWithBN(nn.Module):\n    def __init__(self):\n        super(CNNWithBN, self).__init__()\n        self.conv1 = nn.Conv2d(3, 64, 3, padding=1)\n        self.bn1 = nn.BatchNorm2d(64)\n        \n        self.conv2 = nn.Conv2d(64, 128, 3, padding=1)\n        self.bn2 = nn.BatchNorm2d(128)\n        \n        self.conv3 = nn.Conv2d(128, 256, 3, padding=1)\n        self.bn3 = nn.BatchNorm2d(256)\n        \n        self.pool = nn.MaxPool2d(2, 2)\n        self.fc1 = nn.Linear(256 * 4 * 4, 512)\n        self.bn_fc = nn.BatchNorm1d(512)\n        self.fc2 = nn.Linear(512, 10)\n        self.relu = nn.ReLU()\n        # Dropout менший або взагалі не потрібен з BN\n        self.dropout = nn.Dropout(0.2)\n    \n    def forward(self, x):\n        x = self.conv1(x)\n        x = self.bn1(x)\n        x = self.relu(x)\n        x = self.pool(x)\n        \n        x = self.conv2(x)\n        x = self.bn2(x)\n        x = self.relu(x)\n        x = self.pool(x)\n        \n        x = self.conv3(x)\n        x = self.bn3(x)\n        x = self.relu(x)\n        x = self.pool(x)\n        \n        x = x.view(x.size(0), -1)\n        x = self.fc1(x)\n        x = self.bn_fc(x)\n        x = self.relu(x)\n        x = self.dropout(x)\n        x = self.fc2(x)\n        return x\n\n# Завантаження CIFAR-10\ntransform_train = transforms.Compose([\n    transforms.RandomHorizontalFlip(),\n    transforms.RandomCrop(32, padding=4),\n    transforms.ToTensor(),\n    transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010))\n])\n\ntransform_test = transforms.Compose([\n    transforms.ToTensor(),\n    transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010))\n])\n\ntrain_dataset = datasets.CIFAR10('.\u002Fdata', train=True, download=True, transform=transform_train)\ntest_dataset = datasets.CIFAR10('.\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\nprint(\"✅ Датасет завантажено\")\nprint(f\"   Train: {len(train_dataset)} зображень\")\nprint(f\"   Test:  {len(test_dataset)} зображень\")\n",[5365,9923,9924,9930,9940,9950,9960,9970,9977,9981,9986,10003,10015,10030,10056,10082,10109,10123,10147,10161,10167,10181,10185,10201,10214,10223,10236,10244,10257,10265,10277,10295,10303,10309,10313,10318,10334,10346,10360,10386,10396,10400,10426,10436,10440,10466,10477,10481,10495,10517,10528,10542,10548,10553,10563,10567,10583,10592,10601,10609,10617,10621,10630,10638,10646,10654,10658,10667,10676,10684,10692,10696,10708,10716,10725,10733,10742,10750,10756,10760,10766,10772,10778,10797,10802,10838,10843,10848,10854,10859,10888,10893,10898,10929,10960,10965,10995,11025,11030,11042,11068],{"__ignoreMap":5363},[5368,9925,9926,9928],{"class":5370,"line":5371},[5368,9927,5561],{"class":5560},[5368,9929,5564],{"class":5381},[5368,9931,9932,9934,9936,9938],{"class":5370,"line":5378},[5368,9933,5561],{"class":5560},[5368,9935,5571],{"class":5381},[5368,9937,5574],{"class":5560},[5368,9939,5577],{"class":5381},[5368,9941,9942,9944,9946,9948],{"class":5370,"line":5410},[5368,9943,5561],{"class":5560},[5368,9945,5584],{"class":5381},[5368,9947,5574],{"class":5560},[5368,9949,5589],{"class":5381},[5368,9951,9952,9954,9956,9958],{"class":5370,"line":5592},[5368,9953,5595],{"class":5560},[5368,9955,5598],{"class":5381},[5368,9957,5561],{"class":5560},[5368,9959,5603],{"class":5381},[5368,9961,9962,9964,9966,9968],{"class":5370,"line":5606},[5368,9963,5595],{"class":5560},[5368,9965,5611],{"class":5381},[5368,9967,5561],{"class":5560},[5368,9969,5616],{"class":5381},[5368,9971,9972,9974],{"class":5370,"line":5619},[5368,9973,5561],{"class":5560},[5368,9975,9976],{"class":5381}," time\n",[5368,9978,9979],{"class":5370,"line":5632},[5368,9980,5649],{"emptyLinePlaceholder":5648},[5368,9982,9983],{"class":5370,"line":5645},[5368,9984,9985],{"class":5374},"# Модель БЕЗ Batch Normalization\n",[5368,9987,9988,9990,9993,9995,9997,9999,10001],{"class":5370,"line":5652},[5368,9989,5662],{"class":5661},[5368,9991,9992],{"class":5665}," CNNBaseline",[5368,9994,5669],{"class":5381},[5368,9996,5672],{"class":5665},[5368,9998,5497],{"class":5381},[5368,10000,5677],{"class":5665},[5368,10002,5680],{"class":5381},[5368,10004,10005,10007,10009,10011,10013],{"class":5370,"line":5658},[5368,10006,5686],{"class":5661},[5368,10008,5690],{"class":5689},[5368,10010,5669],{"class":5381},[5368,10012,5695],{"class":5385},[5368,10014,5680],{"class":5381},[5368,10016,10017,10019,10022,10024,10026,10028],{"class":5370,"line":5683},[5368,10018,5703],{"class":5665},[5368,10020,10021],{"class":5381},"(CNNBaseline, ",[5368,10023,5695],{"class":5661},[5368,10025,5711],{"class":5381},[5368,10027,5714],{"class":5689},[5368,10029,5717],{"class":5381},[5368,10031,10032,10034,10036,10038,10040,10042,10044,10046,10048,10050,10052,10054],{"class":5370,"line":5700},[5368,10033,5723],{"class":5661},[5368,10035,7677],{"class":5381},[5368,10037,7680],{"class":5392},[5368,10039,5396],{"class":5381},[5368,10041,7685],{"class":5392},[5368,10043,5396],{"class":5381},[5368,10045,7680],{"class":5392},[5368,10047,5396],{"class":5381},[5368,10049,7699],{"class":5385},[5368,10051,5846],{"class":5381},[5368,10053,5549],{"class":5392},[5368,10055,5737],{"class":5381},[5368,10057,10058,10060,10062,10064,10066,10068,10070,10072,10074,10076,10078,10080],{"class":5370,"line":5720},[5368,10059,5723],{"class":5661},[5368,10061,9378],{"class":5381},[5368,10063,7685],{"class":5392},[5368,10065,5396],{"class":5381},[5368,10067,5788],{"class":5392},[5368,10069,5396],{"class":5381},[5368,10071,7680],{"class":5392},[5368,10073,5396],{"class":5381},[5368,10075,7699],{"class":5385},[5368,10077,5846],{"class":5381},[5368,10079,5549],{"class":5392},[5368,10081,5737],{"class":5381},[5368,10083,10084,10086,10089,10091,10093,10095,10097,10099,10101,10103,10105,10107],{"class":5370,"line":5740},[5368,10085,5723],{"class":5661},[5368,10087,10088],{"class":5381},".conv3 = nn.Conv2d(",[5368,10090,5788],{"class":5392},[5368,10092,5396],{"class":5381},[5368,10094,5734],{"class":5392},[5368,10096,5396],{"class":5381},[5368,10098,7680],{"class":5392},[5368,10100,5396],{"class":5381},[5368,10102,7699],{"class":5385},[5368,10104,5846],{"class":5381},[5368,10106,5549],{"class":5392},[5368,10108,5737],{"class":5381},[5368,10110,10111,10113,10115,10117,10119,10121],{"class":5370,"line":5756},[5368,10112,5723],{"class":5661},[5368,10114,7729],{"class":5381},[5368,10116,6558],{"class":5392},[5368,10118,5396],{"class":5381},[5368,10120,6558],{"class":5392},[5368,10122,5737],{"class":5381},[5368,10124,10125,10127,10129,10131,10133,10136,10138,10140,10142,10145],{"class":5370,"line":5776},[5368,10126,5723],{"class":5661},[5368,10128,5726],{"class":5381},[5368,10130,5734],{"class":5392},[5368,10132,9454],{"class":5381},[5368,10134,10135],{"class":5392},"4",[5368,10137,9454],{"class":5381},[5368,10139,10135],{"class":5392},[5368,10141,5396],{"class":5381},[5368,10143,10144],{"class":5392},"512",[5368,10146,5737],{"class":5381},[5368,10148,10149,10151,10153,10155,10157,10159],{"class":5370,"line":5793},[5368,10150,5723],{"class":5661},[5368,10152,5745],{"class":5381},[5368,10154,10144],{"class":5392},[5368,10156,5396],{"class":5381},[5368,10158,5805],{"class":5392},[5368,10160,5737],{"class":5381},[5368,10162,10163,10165],{"class":5370,"line":5810},[5368,10164,5723],{"class":5661},[5368,10166,5815],{"class":5381},[5368,10168,10169,10171,10174,10176,10178],{"class":5370,"line":5818},[5368,10170,5723],{"class":5661},[5368,10172,10173],{"class":5381},".dropout = nn.Dropout(",[5368,10175,6705],{"class":5392},[5368,10177,5770],{"class":5381},[5368,10179,10180],{"class":5374},"# Потрібен Dropout для регуляризації\n",[5368,10182,10183],{"class":5370,"line":5824},[5368,10184,5821],{"class":5381},[5368,10186,10187,10189,10191,10193,10195,10197,10199],{"class":5370,"line":5854},[5368,10188,5686],{"class":5661},[5368,10190,5829],{"class":5689},[5368,10192,5669],{"class":5381},[5368,10194,5695],{"class":5385},[5368,10196,5396],{"class":5381},[5368,10198,5838],{"class":5385},[5368,10200,5680],{"class":5381},[5368,10202,10203,10205,10207,10209,10211],{"class":5370,"line":5870},[5368,10204,5873],{"class":5381},[5368,10206,5695],{"class":5661},[5368,10208,5878],{"class":5381},[5368,10210,5695],{"class":5661},[5368,10212,10213],{"class":5381},".conv1(x))\n",[5368,10215,10216,10218,10220],{"class":5370,"line":5886},[5368,10217,5873],{"class":5381},[5368,10219,5695],{"class":5661},[5368,10221,10222],{"class":5381},".pool(x)\n",[5368,10224,10225,10227,10229,10231,10233],{"class":5370,"line":5900},[5368,10226,5873],{"class":5381},[5368,10228,5695],{"class":5661},[5368,10230,5878],{"class":5381},[5368,10232,5695],{"class":5661},[5368,10234,10235],{"class":5381},".conv2(x))\n",[5368,10237,10238,10240,10242],{"class":5370,"line":5909},[5368,10239,5873],{"class":5381},[5368,10241,5695],{"class":5661},[5368,10243,10222],{"class":5381},[5368,10245,10246,10248,10250,10252,10254],{"class":5370,"line":5923},[5368,10247,5873],{"class":5381},[5368,10249,5695],{"class":5661},[5368,10251,5878],{"class":5381},[5368,10253,5695],{"class":5661},[5368,10255,10256],{"class":5381},".conv3(x))\n",[5368,10258,10259,10261,10263],{"class":5370,"line":5937},[5368,10260,5873],{"class":5381},[5368,10262,5695],{"class":5661},[5368,10264,10222],{"class":5381},[5368,10266,10267,10269,10271,10273,10275],{"class":5370,"line":5947},[5368,10268,5857],{"class":5381},[5368,10270,5860],{"class":5392},[5368,10272,5863],{"class":5381},[5368,10274,5549],{"class":5392},[5368,10276,5737],{"class":5381},[5368,10278,10279,10281,10283,10286,10288,10290,10292],{"class":5370,"line":5953},[5368,10280,5873],{"class":5381},[5368,10282,5695],{"class":5661},[5368,10284,10285],{"class":5381},".dropout(",[5368,10287,5695],{"class":5661},[5368,10289,5878],{"class":5381},[5368,10291,5695],{"class":5661},[5368,10293,10294],{"class":5381},".fc1(x)))\n",[5368,10296,10297,10299,10301],{"class":5370,"line":5962},[5368,10298,5873],{"class":5381},[5368,10300,5695],{"class":5661},[5368,10302,9038],{"class":5381},[5368,10304,10305,10307],{"class":5370,"line":5971},[5368,10306,5974],{"class":5560},[5368,10308,5977],{"class":5381},[5368,10310,10311],{"class":5370,"line":5980},[5368,10312,5649],{"emptyLinePlaceholder":5648},[5368,10314,10315],{"class":5370,"line":5985},[5368,10316,10317],{"class":5374},"# Модель З Batch Normalization\n",[5368,10319,10320,10322,10324,10326,10328,10330,10332],{"class":5370,"line":5991},[5368,10321,5662],{"class":5661},[5368,10323,9277],{"class":5665},[5368,10325,5669],{"class":5381},[5368,10327,5672],{"class":5665},[5368,10329,5497],{"class":5381},[5368,10331,5677],{"class":5665},[5368,10333,5680],{"class":5381},[5368,10335,10336,10338,10340,10342,10344],{"class":5370,"line":6015},[5368,10337,5686],{"class":5661},[5368,10339,5690],{"class":5689},[5368,10341,5669],{"class":5381},[5368,10343,5695],{"class":5385},[5368,10345,5680],{"class":5381},[5368,10347,10348,10350,10352,10354,10356,10358],{"class":5370,"line":6021},[5368,10349,5703],{"class":5665},[5368,10351,9306],{"class":5381},[5368,10353,5695],{"class":5661},[5368,10355,5711],{"class":5381},[5368,10357,5714],{"class":5689},[5368,10359,5717],{"class":5381},[5368,10361,10362,10364,10366,10368,10370,10372,10374,10376,10378,10380,10382,10384],{"class":5370,"line":6027},[5368,10363,5723],{"class":5661},[5368,10365,7677],{"class":5381},[5368,10367,7680],{"class":5392},[5368,10369,5396],{"class":5381},[5368,10371,7685],{"class":5392},[5368,10373,5396],{"class":5381},[5368,10375,7680],{"class":5392},[5368,10377,5396],{"class":5381},[5368,10379,7699],{"class":5385},[5368,10381,5846],{"class":5381},[5368,10383,5549],{"class":5392},[5368,10385,5737],{"class":5381},[5368,10387,10388,10390,10392,10394],{"class":5370,"line":6053},[5368,10389,5723],{"class":5661},[5368,10391,7712],{"class":5381},[5368,10393,7685],{"class":5392},[5368,10395,5737],{"class":5381},[5368,10397,10398],{"class":5370,"line":6058},[5368,10399,5950],{"class":5381},[5368,10401,10402,10404,10406,10408,10410,10412,10414,10416,10418,10420,10422,10424],{"class":5370,"line":6064},[5368,10403,5723],{"class":5661},[5368,10405,9378],{"class":5381},[5368,10407,7685],{"class":5392},[5368,10409,5396],{"class":5381},[5368,10411,5788],{"class":5392},[5368,10413,5396],{"class":5381},[5368,10415,7680],{"class":5392},[5368,10417,5396],{"class":5381},[5368,10419,7699],{"class":5385},[5368,10421,5846],{"class":5381},[5368,10423,5549],{"class":5392},[5368,10425,5737],{"class":5381},[5368,10427,10428,10430,10432,10434],{"class":5370,"line":6070},[5368,10429,5723],{"class":5661},[5368,10431,9409],{"class":5381},[5368,10433,5788],{"class":5392},[5368,10435,5737],{"class":5381},[5368,10437,10438],{"class":5370,"line":6076},[5368,10439,5950],{"class":5381},[5368,10441,10442,10444,10446,10448,10450,10452,10454,10456,10458,10460,10462,10464],{"class":5370,"line":6094},[5368,10443,5723],{"class":5661},[5368,10445,10088],{"class":5381},[5368,10447,5788],{"class":5392},[5368,10449,5396],{"class":5381},[5368,10451,5734],{"class":5392},[5368,10453,5396],{"class":5381},[5368,10455,7680],{"class":5392},[5368,10457,5396],{"class":5381},[5368,10459,7699],{"class":5385},[5368,10461,5846],{"class":5381},[5368,10463,5549],{"class":5392},[5368,10465,5737],{"class":5381},[5368,10467,10468,10470,10473,10475],{"class":5370,"line":6099},[5368,10469,5723],{"class":5661},[5368,10471,10472],{"class":5381},".bn3 = nn.BatchNorm2d(",[5368,10474,5734],{"class":5392},[5368,10476,5737],{"class":5381},[5368,10478,10479],{"class":5370,"line":6135},[5368,10480,5950],{"class":5381},[5368,10482,10483,10485,10487,10489,10491,10493],{"class":5370,"line":6159},[5368,10484,5723],{"class":5661},[5368,10486,7729],{"class":5381},[5368,10488,6558],{"class":5392},[5368,10490,5396],{"class":5381},[5368,10492,6558],{"class":5392},[5368,10494,5737],{"class":5381},[5368,10496,10497,10499,10501,10503,10505,10507,10509,10511,10513,10515],{"class":5370,"line":6164},[5368,10498,5723],{"class":5661},[5368,10500,5726],{"class":5381},[5368,10502,5734],{"class":5392},[5368,10504,9454],{"class":5381},[5368,10506,10135],{"class":5392},[5368,10508,9454],{"class":5381},[5368,10510,10135],{"class":5392},[5368,10512,5396],{"class":5381},[5368,10514,10144],{"class":5392},[5368,10516,5737],{"class":5381},[5368,10518,10519,10521,10524,10526],{"class":5370,"line":6170},[5368,10520,5723],{"class":5661},[5368,10522,10523],{"class":5381},".bn_fc = nn.BatchNorm1d(",[5368,10525,10144],{"class":5392},[5368,10527,5737],{"class":5381},[5368,10529,10530,10532,10534,10536,10538,10540],{"class":5370,"line":6176},[5368,10531,5723],{"class":5661},[5368,10533,5745],{"class":5381},[5368,10535,10144],{"class":5392},[5368,10537,5396],{"class":5381},[5368,10539,5805],{"class":5392},[5368,10541,5737],{"class":5381},[5368,10543,10544,10546],{"class":5370,"line":6182},[5368,10545,5723],{"class":5661},[5368,10547,5815],{"class":5381},[5368,10549,10550],{"class":5370,"line":6187},[5368,10551,10552],{"class":5374},"        # Dropout менший або взагалі не потрібен з BN\n",[5368,10554,10555,10557,10559,10561],{"class":5370,"line":6193},[5368,10556,5723],{"class":5661},[5368,10558,10173],{"class":5381},[5368,10560,6766],{"class":5392},[5368,10562,5737],{"class":5381},[5368,10564,10565],{"class":5370,"line":6211},[5368,10566,5821],{"class":5381},[5368,10568,10569,10571,10573,10575,10577,10579,10581],{"class":5370,"line":6229},[5368,10570,5686],{"class":5661},[5368,10572,5829],{"class":5689},[5368,10574,5669],{"class":5381},[5368,10576,5695],{"class":5385},[5368,10578,5396],{"class":5381},[5368,10580,5838],{"class":5385},[5368,10582,5680],{"class":5381},[5368,10584,10585,10587,10589],{"class":5370,"line":6235},[5368,10586,5873],{"class":5381},[5368,10588,5695],{"class":5661},[5368,10590,10591],{"class":5381},".conv1(x)\n",[5368,10593,10594,10596,10598],{"class":5370,"line":6240},[5368,10595,5873],{"class":5381},[5368,10597,5695],{"class":5661},[5368,10599,10600],{"class":5381},".bn1(x)\n",[5368,10602,10603,10605,10607],{"class":5370,"line":6246},[5368,10604,5873],{"class":5381},[5368,10606,5695],{"class":5661},[5368,10608,9025],{"class":5381},[5368,10610,10611,10613,10615],{"class":5370,"line":6251},[5368,10612,5873],{"class":5381},[5368,10614,5695],{"class":5661},[5368,10616,10222],{"class":5381},[5368,10618,10619],{"class":5370,"line":6257},[5368,10620,5950],{"class":5381},[5368,10622,10623,10625,10627],{"class":5370,"line":6271},[5368,10624,5873],{"class":5381},[5368,10626,5695],{"class":5661},[5368,10628,10629],{"class":5381},".conv2(x)\n",[5368,10631,10632,10634,10636],{"class":5370,"line":6277},[5368,10633,5873],{"class":5381},[5368,10635,5695],{"class":5661},[5368,10637,9047],{"class":5381},[5368,10639,10640,10642,10644],{"class":5370,"line":6282},[5368,10641,5873],{"class":5381},[5368,10643,5695],{"class":5661},[5368,10645,9025],{"class":5381},[5368,10647,10648,10650,10652],{"class":5370,"line":6288},[5368,10649,5873],{"class":5381},[5368,10651,5695],{"class":5661},[5368,10653,10222],{"class":5381},[5368,10655,10656],{"class":5370,"line":6294},[5368,10657,5950],{"class":5381},[5368,10659,10660,10662,10664],{"class":5370,"line":6300},[5368,10661,5873],{"class":5381},[5368,10663,5695],{"class":5661},[5368,10665,10666],{"class":5381},".conv3(x)\n",[5368,10668,10669,10671,10673],{"class":5370,"line":6306},[5368,10670,5873],{"class":5381},[5368,10672,5695],{"class":5661},[5368,10674,10675],{"class":5381},".bn3(x)\n",[5368,10677,10678,10680,10682],{"class":5370,"line":6311},[5368,10679,5873],{"class":5381},[5368,10681,5695],{"class":5661},[5368,10683,9025],{"class":5381},[5368,10685,10686,10688,10690],{"class":5370,"line":6317},[5368,10687,5873],{"class":5381},[5368,10689,5695],{"class":5661},[5368,10691,10222],{"class":5381},[5368,10693,10694],{"class":5370,"line":6326},[5368,10695,5950],{"class":5381},[5368,10697,10698,10700,10702,10704,10706],{"class":5370,"line":6332},[5368,10699,5857],{"class":5381},[5368,10701,5860],{"class":5392},[5368,10703,5863],{"class":5381},[5368,10705,5549],{"class":5392},[5368,10707,5737],{"class":5381},[5368,10709,10710,10712,10714],{"class":5370,"line":6338},[5368,10711,5873],{"class":5381},[5368,10713,5695],{"class":5661},[5368,10715,9005],{"class":5381},[5368,10717,10718,10720,10722],{"class":5370,"line":6344},[5368,10719,5873],{"class":5381},[5368,10721,5695],{"class":5661},[5368,10723,10724],{"class":5381},".bn_fc(x)\n",[5368,10726,10727,10729,10731],{"class":5370,"line":6350},[5368,10728,5873],{"class":5381},[5368,10730,5695],{"class":5661},[5368,10732,9025],{"class":5381},[5368,10734,10735,10737,10739],{"class":5370,"line":6355},[5368,10736,5873],{"class":5381},[5368,10738,5695],{"class":5661},[5368,10740,10741],{"class":5381},".dropout(x)\n",[5368,10743,10744,10746,10748],{"class":5370,"line":6386},[5368,10745,5873],{"class":5381},[5368,10747,5695],{"class":5661},[5368,10749,9038],{"class":5381},[5368,10751,10752,10754],{"class":5370,"line":6416},[5368,10753,5974],{"class":5560},[5368,10755,5977],{"class":5381},[5368,10757,10758],{"class":5370,"line":6443},[5368,10759,5649],{"emptyLinePlaceholder":5648},[5368,10761,10763],{"class":5370,"line":10762},78,[5368,10764,10765],{"class":5374},"# Завантаження CIFAR-10\n",[5368,10767,10769],{"class":5370,"line":10768},79,[5368,10770,10771],{"class":5381},"transform_train = transforms.Compose([\n",[5368,10773,10775],{"class":5370,"line":10774},80,[5368,10776,10777],{"class":5381},"    transforms.RandomHorizontalFlip(),\n",[5368,10779,10781,10784,10787,10789,10791,10793,10795],{"class":5370,"line":10780},81,[5368,10782,10783],{"class":5381},"    transforms.RandomCrop(",[5368,10785,10786],{"class":5392},"32",[5368,10788,5396],{"class":5381},[5368,10790,7699],{"class":5385},[5368,10792,5846],{"class":5381},[5368,10794,10135],{"class":5392},[5368,10796,8166],{"class":5381},[5368,10798,10800],{"class":5370,"line":10799},82,[5368,10801,6073],{"class":5381},[5368,10803,10805,10807,10810,10812,10815,10817,10820,10823,10826,10828,10831,10833,10836],{"class":5370,"line":10804},83,[5368,10806,6079],{"class":5381},[5368,10808,10809],{"class":5392},"0.4914",[5368,10811,5396],{"class":5381},[5368,10813,10814],{"class":5392},"0.4822",[5368,10816,5396],{"class":5381},[5368,10818,10819],{"class":5392},"0.4465",[5368,10821,10822],{"class":5381},"), (",[5368,10824,10825],{"class":5392},"0.2023",[5368,10827,5396],{"class":5381},[5368,10829,10830],{"class":5392},"0.1994",[5368,10832,5396],{"class":5381},[5368,10834,10835],{"class":5392},"0.2010",[5368,10837,6599],{"class":5381},[5368,10839,10841],{"class":5370,"line":10840},84,[5368,10842,5431],{"class":5381},[5368,10844,10846],{"class":5370,"line":10845},85,[5368,10847,5649],{"emptyLinePlaceholder":5648},[5368,10849,10851],{"class":5370,"line":10850},86,[5368,10852,10853],{"class":5381},"transform_test = transforms.Compose([\n",[5368,10855,10857],{"class":5370,"line":10856},87,[5368,10858,6073],{"class":5381},[5368,10860,10862,10864,10866,10868,10870,10872,10874,10876,10878,10880,10882,10884,10886],{"class":5370,"line":10861},88,[5368,10863,6079],{"class":5381},[5368,10865,10809],{"class":5392},[5368,10867,5396],{"class":5381},[5368,10869,10814],{"class":5392},[5368,10871,5396],{"class":5381},[5368,10873,10819],{"class":5392},[5368,10875,10822],{"class":5381},[5368,10877,10825],{"class":5392},[5368,10879,5396],{"class":5381},[5368,10881,10830],{"class":5392},[5368,10883,5396],{"class":5381},[5368,10885,10835],{"class":5392},[5368,10887,6599],{"class":5381},[5368,10889,10891],{"class":5370,"line":10890},89,[5368,10892,5431],{"class":5381},[5368,10894,10896],{"class":5370,"line":10895},90,[5368,10897,5649],{"emptyLinePlaceholder":5648},[5368,10899,10901,10904,10906,10908,10910,10912,10914,10916,10918,10920,10922,10924,10926],{"class":5370,"line":10900},91,[5368,10902,10903],{"class":5381},"train_dataset = datasets.CIFAR10(",[5368,10905,6105],{"class":5997},[5368,10907,5396],{"class":5381},[5368,10909,6110],{"class":5385},[5368,10911,5846],{"class":5381},[5368,10913,6115],{"class":5661},[5368,10915,5396],{"class":5381},[5368,10917,6120],{"class":5385},[5368,10919,5846],{"class":5381},[5368,10921,6115],{"class":5661},[5368,10923,5396],{"class":5381},[5368,10925,6129],{"class":5385},[5368,10927,10928],{"class":5381},"=transform_train)\n",[5368,10930,10932,10935,10937,10939,10941,10943,10945,10947,10949,10951,10953,10955,10957],{"class":5370,"line":10931},92,[5368,10933,10934],{"class":5381},"test_dataset = datasets.CIFAR10(",[5368,10936,6105],{"class":5997},[5368,10938,5396],{"class":5381},[5368,10940,6110],{"class":5385},[5368,10942,5846],{"class":5381},[5368,10944,5849],{"class":5661},[5368,10946,5396],{"class":5381},[5368,10948,6120],{"class":5385},[5368,10950,5846],{"class":5381},[5368,10952,6115],{"class":5661},[5368,10954,5396],{"class":5381},[5368,10956,6129],{"class":5385},[5368,10958,10959],{"class":5381},"=transform_test)\n",[5368,10961,10963],{"class":5370,"line":10962},93,[5368,10964,5649],{"emptyLinePlaceholder":5648},[5368,10966,10968,10970,10972,10974,10976,10978,10980,10982,10984,10986,10989,10991,10993],{"class":5370,"line":10967},94,[5368,10969,6138],{"class":5381},[5368,10971,6141],{"class":5385},[5368,10973,5846],{"class":5381},[5368,10975,5788],{"class":5392},[5368,10977,5396],{"class":5381},[5368,10979,6150],{"class":5385},[5368,10981,5846],{"class":5381},[5368,10983,6115],{"class":5661},[5368,10985,5396],{"class":5381},[5368,10987,10988],{"class":5385},"num_workers",[5368,10990,5846],{"class":5381},[5368,10992,6558],{"class":5392},[5368,10994,5737],{"class":5381},[5368,10996,10998,11001,11003,11005,11007,11009,11011,11013,11015,11017,11019,11021,11023],{"class":5370,"line":10997},95,[5368,10999,11000],{"class":5381},"test_loader = DataLoader(test_dataset, ",[5368,11002,6141],{"class":5385},[5368,11004,5846],{"class":5381},[5368,11006,5788],{"class":5392},[5368,11008,5396],{"class":5381},[5368,11010,6150],{"class":5385},[5368,11012,5846],{"class":5381},[5368,11014,5849],{"class":5661},[5368,11016,5396],{"class":5381},[5368,11018,10988],{"class":5385},[5368,11020,5846],{"class":5381},[5368,11022,6558],{"class":5392},[5368,11024,5737],{"class":5381},[5368,11026,11028],{"class":5370,"line":11027},96,[5368,11029,5649],{"emptyLinePlaceholder":5648},[5368,11031,11033,11035,11037,11040],{"class":5370,"line":11032},97,[5368,11034,6358],{"class":5689},[5368,11036,5669],{"class":5381},[5368,11038,11039],{"class":5997},"\"✅ Датасет завантажено\"",[5368,11041,5737],{"class":5381},[5368,11043,11045,11047,11049,11051,11054,11056,11058,11061,11063,11066],{"class":5370,"line":11044},98,[5368,11046,6358],{"class":5689},[5368,11048,5669],{"class":5381},[5368,11050,6363],{"class":5661},[5368,11052,11053],{"class":5997},"\"   Train: ",[5368,11055,6369],{"class":5661},[5368,11057,6372],{"class":5689},[5368,11059,11060],{"class":5381},"(train_dataset)",[5368,11062,6378],{"class":5661},[5368,11064,11065],{"class":5997}," зображень\"",[5368,11067,5737],{"class":5381},[5368,11069,11071,11073,11075,11077,11080,11082,11084,11087,11089,11091],{"class":5370,"line":11070},99,[5368,11072,6358],{"class":5689},[5368,11074,5669],{"class":5381},[5368,11076,6363],{"class":5661},[5368,11078,11079],{"class":5997},"\"   Test:  ",[5368,11081,6369],{"class":5661},[5368,11083,6372],{"class":5689},[5368,11085,11086],{"class":5381},"(test_dataset)",[5368,11088,6378],{"class":5661},[5368,11090,11065],{"class":5997},[5368,11092,5737],{"class":5381},[6478,11094,11095,11100],{"v-slot:output":5363},[5191,11096,6482,11097],{},[5195,11098,11099],{},"Датасет завантажено",[5247,11101,11102,11105],{},[5250,11103,11104],{},"Train: 50,000 зображень (32×32×3, 10 класів)",[5250,11106,11107],{},"Test: 10,000 зображень",[5537,11109,11111,12007],{"execution-count":6558,"execution-time":11110},"480.5s",[5358,11112,11114],{"className":5360,"code":11113,"language":5362,"meta":5363,"style":5363},"def train_and_evaluate(model, model_name, train_loader, test_loader, \n                      epochs=20, lr=0.01, device='cuda'):\n    \"\"\"Навчання моделі та збереження метрик\"\"\"\n    model = model.to(device)\n    criterion = nn.CrossEntropyLoss()\n    optimizer = optim.SGD(model.parameters(), lr=lr, momentum=0.9, weight_decay=5e-4)\n    scheduler = optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=epochs)\n    \n    history = {\n        'train_loss': [], 'train_acc': [],\n        'test_loss': [], 'test_acc': [],\n        'epoch_time': []\n    }\n    \n    print(f\"\\n🚀 Навчання моделі: {model_name}\")\n    print(f\"   Learning rate: {lr}\")\n    \n    for epoch in range(epochs):\n        start_time = time.time()\n        \n        # Training\n        model.train()\n        train_loss = 0.0\n        train_correct = 0\n        train_total = 0\n        \n        for images, labels in train_loader:\n            images, labels = images.to(device), labels.to(device)\n            \n            outputs = model(images)\n            loss = criterion(outputs, labels)\n            \n            optimizer.zero_grad()\n            loss.backward()\n            optimizer.step()\n            \n            train_loss += loss.item()\n            _, predicted = outputs.max(1)\n            train_total += labels.size(0)\n            train_correct += predicted.eq(labels).sum().item()\n        \n        # Evaluation\n        model.eval()\n        test_loss = 0.0\n        test_correct = 0\n        test_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                test_loss += loss.item()\n                _, predicted = outputs.max(1)\n                test_total += labels.size(0)\n                test_correct += predicted.eq(labels).sum().item()\n        \n        epoch_time = time.time() - start_time\n        train_loss_avg = train_loss \u002F len(train_loader)\n        train_acc = 100. * train_correct \u002F train_total\n        test_loss_avg = test_loss \u002F len(test_loader)\n        test_acc = 100. * test_correct \u002F test_total\n        \n        history['train_loss'].append(train_loss_avg)\n        history['train_acc'].append(train_acc)\n        history['test_loss'].append(test_loss_avg)\n        history['test_acc'].append(test_acc)\n        history['epoch_time'].append(epoch_time)\n        \n        scheduler.step()\n        \n        if (epoch + 1) % 5 == 0:\n            print(f\"   Епоха {epoch+1:2d}\u002F{epochs}: \"\n                  f\"Train Acc={train_acc:.2f}%, Test Acc={test_acc:.2f}%, \"\n                  f\"Time={epoch_time:.1f}s\")\n    \n    return history\n\n# Експеримент\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n\n# Модель 1: Baseline без BN\ntorch.manual_seed(42)\nmodel_baseline = CNNBaseline()\nhistory_baseline = train_and_evaluate(\n    model_baseline, \"Baseline (без BN)\", \n    train_loader, test_loader, \n    epochs=20, lr=0.01, device=device\n)\n\n# Модель 2: З Batch Normalization\ntorch.manual_seed(42)\nmodel_bn = CNNWithBN()\nhistory_bn = train_and_evaluate(\n    model_bn, \"CNN + BatchNorm\", \n    train_loader, test_loader, \n    epochs=20, lr=0.1,  # ← ЗБІЛЬШЕНИЙ LR у 10 разів!\n    device=device\n)\n\nprint(\"\\n🎉 Експеримент завершено!\")\n",[5365,11115,11116,11146,11175,11180,11185,11190,11218,11229,11233,11238,11252,11264,11272,11277,11281,11307,11328,11332,11347,11352,11356,11361,11366,11374,11382,11389,11393,11405,11410,11415,11420,11425,11429,11434,11439,11444,11448,11453,11462,11471,11476,11480,11485,11490,11497,11504,11511,11515,11522,11533,11538,11543,11548,11553,11558,11567,11576,11581,11585,11590,11600,11610,11620,11630,11634,11645,11654,11664,11673,11683,11687,11692,11696,11718,11753,11782,11802,11806,11814,11818,11823,11839,11843,11848,11858,11863,11868,11878,11883,11907,11911,11915,11920,11928,11933,11938,11948,11952,11974,11981,11986,11991],{"__ignoreMap":5363},[5368,11117,11118,11121,11124,11126,11129,11131,11134,11136,11139,11141,11144],{"class":5370,"line":5371},[5368,11119,11120],{"class":5661},"def",[5368,11122,11123],{"class":5689}," train_and_evaluate",[5368,11125,5669],{"class":5381},[5368,11127,11128],{"class":5385},"model",[5368,11130,5396],{"class":5381},[5368,11132,11133],{"class":5385},"model_name",[5368,11135,5396],{"class":5381},[5368,11137,11138],{"class":5385},"train_loader",[5368,11140,5396],{"class":5381},[5368,11142,11143],{"class":5385},"test_loader",[5368,11145,6695],{"class":5381},[5368,11147,11148,11151,11153,11156,11158,11160,11162,11164,11166,11169,11171,11173],{"class":5370,"line":5378},[5368,11149,11150],{"class":5385},"                      epochs",[5368,11152,5846],{"class":5381},[5368,11154,11155],{"class":5392},"20",[5368,11157,5396],{"class":5381},[5368,11159,6033],{"class":5385},[5368,11161,5846],{"class":5381},[5368,11163,6038],{"class":5392},[5368,11165,5396],{"class":5381},[5368,11167,11168],{"class":5385},"device",[5368,11170,5846],{"class":5381},[5368,11172,5998],{"class":5997},[5368,11174,5680],{"class":5381},[5368,11176,11177],{"class":5370,"line":5410},[5368,11178,11179],{"class":5997},"    \"\"\"Навчання моделі та збереження метрик\"\"\"\n",[5368,11181,11182],{"class":5370,"line":5592},[5368,11183,11184],{"class":5381},"    model = model.to(device)\n",[5368,11186,11187],{"class":5370,"line":5606},[5368,11188,11189],{"class":5381},"    criterion = nn.CrossEntropyLoss()\n",[5368,11191,11192,11195,11197,11200,11202,11204,11206,11208,11211,11213,11216],{"class":5370,"line":5619},[5368,11193,11194],{"class":5381},"    optimizer = optim.SGD(model.parameters(), ",[5368,11196,6033],{"class":5385},[5368,11198,11199],{"class":5381},"=lr, ",[5368,11201,6043],{"class":5385},[5368,11203,5846],{"class":5381},[5368,11205,6048],{"class":5392},[5368,11207,5396],{"class":5381},[5368,11209,11210],{"class":5385},"weight_decay",[5368,11212,5846],{"class":5381},[5368,11214,11215],{"class":5392},"5e-4",[5368,11217,5737],{"class":5381},[5368,11219,11220,11223,11226],{"class":5370,"line":5632},[5368,11221,11222],{"class":5381},"    scheduler = optim.lr_scheduler.CosineAnnealingLR(optimizer, ",[5368,11224,11225],{"class":5385},"T_max",[5368,11227,11228],{"class":5381},"=epochs)\n",[5368,11230,11231],{"class":5370,"line":5645},[5368,11232,5821],{"class":5381},[5368,11234,11235],{"class":5370,"line":5652},[5368,11236,11237],{"class":5381},"    history = {\n",[5368,11239,11240,11243,11246,11249],{"class":5370,"line":5658},[5368,11241,11242],{"class":5997},"        'train_loss'",[5368,11244,11245],{"class":5381},": [], ",[5368,11247,11248],{"class":5997},"'train_acc'",[5368,11250,11251],{"class":5381},": [],\n",[5368,11253,11254,11257,11259,11262],{"class":5370,"line":5683},[5368,11255,11256],{"class":5997},"        'test_loss'",[5368,11258,11245],{"class":5381},[5368,11260,11261],{"class":5997},"'test_acc'",[5368,11263,11251],{"class":5381},[5368,11265,11266,11269],{"class":5370,"line":5700},[5368,11267,11268],{"class":5997},"        'epoch_time'",[5368,11270,11271],{"class":5381},": []\n",[5368,11273,11274],{"class":5370,"line":5720},[5368,11275,11276],{"class":5381},"    }\n",[5368,11278,11279],{"class":5370,"line":5740},[5368,11280,5821],{"class":5381},[5368,11282,11283,11286,11288,11290,11292,11294,11297,11299,11301,11303,11305],{"class":5370,"line":5756},[5368,11284,11285],{"class":5689},"    print",[5368,11287,5669],{"class":5381},[5368,11289,6363],{"class":5661},[5368,11291,6411],{"class":5997},[5368,11293,8223],{"class":8222},[5368,11295,11296],{"class":5997},"🚀 Навчання моделі: ",[5368,11298,6369],{"class":5661},[5368,11300,11133],{"class":5381},[5368,11302,6378],{"class":5661},[5368,11304,6411],{"class":5997},[5368,11306,5737],{"class":5381},[5368,11308,11309,11311,11313,11315,11318,11320,11322,11324,11326],{"class":5370,"line":5776},[5368,11310,11285],{"class":5689},[5368,11312,5669],{"class":5381},[5368,11314,6363],{"class":5661},[5368,11316,11317],{"class":5997},"\"   Learning rate: ",[5368,11319,6369],{"class":5661},[5368,11321,6033],{"class":5381},[5368,11323,6378],{"class":5661},[5368,11325,6411],{"class":5997},[5368,11327,5737],{"class":5381},[5368,11329,11330],{"class":5370,"line":5793},[5368,11331,5821],{"class":5381},[5368,11333,11334,11336,11339,11341,11344],{"class":5370,"line":5810},[5368,11335,8721],{"class":5560},[5368,11337,11338],{"class":5381}," epoch ",[5368,11340,6202],{"class":5560},[5368,11342,11343],{"class":5689}," range",[5368,11345,11346],{"class":5381},"(epochs):\n",[5368,11348,11349],{"class":5370,"line":5818},[5368,11350,11351],{"class":5381},"        start_time = time.time()\n",[5368,11353,11354],{"class":5370,"line":5824},[5368,11355,5950],{"class":5381},[5368,11357,11358],{"class":5370,"line":5854},[5368,11359,11360],{"class":5374},"        # Training\n",[5368,11362,11363],{"class":5370,"line":5870},[5368,11364,11365],{"class":5381},"        model.train()\n",[5368,11367,11368,11371],{"class":5370,"line":5886},[5368,11369,11370],{"class":5381},"        train_loss = ",[5368,11372,11373],{"class":5392},"0.0\n",[5368,11375,11376,11379],{"class":5370,"line":5900},[5368,11377,11378],{"class":5381},"        train_correct = ",[5368,11380,11381],{"class":5392},"0\n",[5368,11383,11384,11387],{"class":5370,"line":5909},[5368,11385,11386],{"class":5381},"        train_total = ",[5368,11388,11381],{"class":5392},[5368,11390,11391],{"class":5370,"line":5923},[5368,11392,5950],{"class":5381},[5368,11394,11395,11398,11400,11402],{"class":5370,"line":5937},[5368,11396,11397],{"class":5560},"        for",[5368,11399,8669],{"class":5381},[5368,11401,6202],{"class":5560},[5368,11403,11404],{"class":5381}," train_loader:\n",[5368,11406,11407],{"class":5370,"line":5947},[5368,11408,11409],{"class":5381},"            images, labels = images.to(device), labels.to(device)\n",[5368,11411,11412],{"class":5370,"line":5953},[5368,11413,11414],{"class":5381},"            \n",[5368,11416,11417],{"class":5370,"line":5962},[5368,11418,11419],{"class":5381},"            outputs = model(images)\n",[5368,11421,11422],{"class":5370,"line":5971},[5368,11423,11424],{"class":5381},"            loss = criterion(outputs, labels)\n",[5368,11426,11427],{"class":5370,"line":5980},[5368,11428,11414],{"class":5381},[5368,11430,11431],{"class":5370,"line":5985},[5368,11432,11433],{"class":5381},"            optimizer.zero_grad()\n",[5368,11435,11436],{"class":5370,"line":5991},[5368,11437,11438],{"class":5381},"            loss.backward()\n",[5368,11440,11441],{"class":5370,"line":6015},[5368,11442,11443],{"class":5381},"            optimizer.step()\n",[5368,11445,11446],{"class":5370,"line":6021},[5368,11447,11414],{"class":5381},[5368,11449,11450],{"class":5370,"line":6027},[5368,11451,11452],{"class":5381},"            train_loss += loss.item()\n",[5368,11454,11455,11458,11460],{"class":5370,"line":6053},[5368,11456,11457],{"class":5381},"            _, predicted = outputs.max(",[5368,11459,5549],{"class":5392},[5368,11461,5737],{"class":5381},[5368,11463,11464,11467,11469],{"class":5370,"line":6058},[5368,11465,11466],{"class":5381},"            train_total += labels.size(",[5368,11468,5860],{"class":5392},[5368,11470,5737],{"class":5381},[5368,11472,11473],{"class":5370,"line":6064},[5368,11474,11475],{"class":5381},"            train_correct += predicted.eq(labels).sum().item()\n",[5368,11477,11478],{"class":5370,"line":6070},[5368,11479,5950],{"class":5381},[5368,11481,11482],{"class":5370,"line":6076},[5368,11483,11484],{"class":5374},"        # Evaluation\n",[5368,11486,11487],{"class":5370,"line":6094},[5368,11488,11489],{"class":5381},"        model.eval()\n",[5368,11491,11492,11495],{"class":5370,"line":6099},[5368,11493,11494],{"class":5381},"        test_loss = ",[5368,11496,11373],{"class":5392},[5368,11498,11499,11502],{"class":5370,"line":6135},[5368,11500,11501],{"class":5381},"        test_correct = ",[5368,11503,11381],{"class":5392},[5368,11505,11506,11509],{"class":5370,"line":6159},[5368,11507,11508],{"class":5381},"        test_total = ",[5368,11510,11381],{"class":5392},[5368,11512,11513],{"class":5370,"line":6164},[5368,11514,5950],{"class":5381},[5368,11516,11517,11520],{"class":5370,"line":6170},[5368,11518,11519],{"class":5560},"        with",[5368,11521,6323],{"class":5381},[5368,11523,11524,11527,11529,11531],{"class":5370,"line":6176},[5368,11525,11526],{"class":5560},"            for",[5368,11528,8669],{"class":5381},[5368,11530,6202],{"class":5560},[5368,11532,8674],{"class":5381},[5368,11534,11535],{"class":5370,"line":6182},[5368,11536,11537],{"class":5381},"                images, labels = images.to(device), labels.to(device)\n",[5368,11539,11540],{"class":5370,"line":6187},[5368,11541,11542],{"class":5381},"                outputs = model(images)\n",[5368,11544,11545],{"class":5370,"line":6193},[5368,11546,11547],{"class":5381},"                loss = criterion(outputs, labels)\n",[5368,11549,11550],{"class":5370,"line":6211},[5368,11551,11552],{"class":5381},"                \n",[5368,11554,11555],{"class":5370,"line":6229},[5368,11556,11557],{"class":5381},"                test_loss += loss.item()\n",[5368,11559,11560,11563,11565],{"class":5370,"line":6235},[5368,11561,11562],{"class":5381},"                _, predicted = outputs.max(",[5368,11564,5549],{"class":5392},[5368,11566,5737],{"class":5381},[5368,11568,11569,11572,11574],{"class":5370,"line":6240},[5368,11570,11571],{"class":5381},"                test_total += labels.size(",[5368,11573,5860],{"class":5392},[5368,11575,5737],{"class":5381},[5368,11577,11578],{"class":5370,"line":6246},[5368,11579,11580],{"class":5381},"                test_correct += predicted.eq(labels).sum().item()\n",[5368,11582,11583],{"class":5370,"line":6251},[5368,11584,5950],{"class":5381},[5368,11586,11587],{"class":5370,"line":6257},[5368,11588,11589],{"class":5381},"        epoch_time = time.time() - start_time\n",[5368,11591,11592,11595,11597],{"class":5370,"line":6271},[5368,11593,11594],{"class":5381},"        train_loss_avg = train_loss \u002F ",[5368,11596,6372],{"class":5689},[5368,11598,11599],{"class":5381},"(train_loader)\n",[5368,11601,11602,11605,11607],{"class":5370,"line":6277},[5368,11603,11604],{"class":5381},"        train_acc = ",[5368,11606,6220],{"class":5392},[5368,11608,11609],{"class":5381},". * train_correct \u002F train_total\n",[5368,11611,11612,11615,11617],{"class":5370,"line":6282},[5368,11613,11614],{"class":5381},"        test_loss_avg = test_loss \u002F ",[5368,11616,6372],{"class":5689},[5368,11618,11619],{"class":5381},"(test_loader)\n",[5368,11621,11622,11625,11627],{"class":5370,"line":6288},[5368,11623,11624],{"class":5381},"        test_acc = ",[5368,11626,6220],{"class":5392},[5368,11628,11629],{"class":5381},". * test_correct \u002F test_total\n",[5368,11631,11632],{"class":5370,"line":6294},[5368,11633,5950],{"class":5381},[5368,11635,11636,11639,11642],{"class":5370,"line":6300},[5368,11637,11638],{"class":5381},"        history[",[5368,11640,11641],{"class":5997},"'train_loss'",[5368,11643,11644],{"class":5381},"].append(train_loss_avg)\n",[5368,11646,11647,11649,11651],{"class":5370,"line":6306},[5368,11648,11638],{"class":5381},[5368,11650,11248],{"class":5997},[5368,11652,11653],{"class":5381},"].append(train_acc)\n",[5368,11655,11656,11658,11661],{"class":5370,"line":6311},[5368,11657,11638],{"class":5381},[5368,11659,11660],{"class":5997},"'test_loss'",[5368,11662,11663],{"class":5381},"].append(test_loss_avg)\n",[5368,11665,11666,11668,11670],{"class":5370,"line":6317},[5368,11667,11638],{"class":5381},[5368,11669,11261],{"class":5997},[5368,11671,11672],{"class":5381},"].append(test_acc)\n",[5368,11674,11675,11677,11680],{"class":5370,"line":6326},[5368,11676,11638],{"class":5381},[5368,11678,11679],{"class":5997},"'epoch_time'",[5368,11681,11682],{"class":5381},"].append(epoch_time)\n",[5368,11684,11685],{"class":5370,"line":6332},[5368,11686,5950],{"class":5381},[5368,11688,11689],{"class":5370,"line":6338},[5368,11690,11691],{"class":5381},"        scheduler.step()\n",[5368,11693,11694],{"class":5370,"line":6344},[5368,11695,5950],{"class":5381},[5368,11697,11698,11700,11703,11705,11708,11710,11713,11715],{"class":5370,"line":6350},[5368,11699,5956],{"class":5560},[5368,11701,11702],{"class":5381}," (epoch + ",[5368,11704,5549],{"class":5392},[5368,11706,11707],{"class":5381},") % ",[5368,11709,6596],{"class":5392},[5368,11711,11712],{"class":5381}," == ",[5368,11714,5860],{"class":5392},[5368,11716,11717],{"class":5381},":\n",[5368,11719,11720,11723,11725,11727,11730,11732,11735,11737,11740,11743,11745,11748,11750],{"class":5370,"line":6355},[5368,11721,11722],{"class":5689},"            print",[5368,11724,5669],{"class":5381},[5368,11726,6363],{"class":5661},[5368,11728,11729],{"class":5997},"\"   Епоха ",[5368,11731,6369],{"class":5661},[5368,11733,11734],{"class":5381},"epoch+",[5368,11736,5549],{"class":5392},[5368,11738,11739],{"class":5661},":2d}",[5368,11741,11742],{"class":5997},"\u002F",[5368,11744,6369],{"class":5661},[5368,11746,11747],{"class":5381},"epochs",[5368,11749,6378],{"class":5661},[5368,11751,11752],{"class":5997},": \"\n",[5368,11754,11755,11758,11761,11763,11766,11769,11772,11774,11777,11779],{"class":5370,"line":6386},[5368,11756,11757],{"class":5661},"                  f",[5368,11759,11760],{"class":5997},"\"Train Acc=",[5368,11762,6369],{"class":5661},[5368,11764,11765],{"class":5381},"train_acc",[5368,11767,11768],{"class":5661},":.2f}",[5368,11770,11771],{"class":5997},"%, Test Acc=",[5368,11773,6369],{"class":5661},[5368,11775,11776],{"class":5381},"test_acc",[5368,11778,11768],{"class":5661},[5368,11780,11781],{"class":5997},"%, \"\n",[5368,11783,11784,11786,11789,11791,11794,11797,11800],{"class":5370,"line":6416},[5368,11785,11757],{"class":5661},[5368,11787,11788],{"class":5997},"\"Time=",[5368,11790,6369],{"class":5661},[5368,11792,11793],{"class":5381},"epoch_time",[5368,11795,11796],{"class":5661},":.1f}",[5368,11798,11799],{"class":5997},"s\"",[5368,11801,5737],{"class":5381},[5368,11803,11804],{"class":5370,"line":6443},[5368,11805,5821],{"class":5381},[5368,11807,11808,11811],{"class":5370,"line":10762},[5368,11809,11810],{"class":5560},"    return",[5368,11812,11813],{"class":5381}," history\n",[5368,11815,11816],{"class":5370,"line":10768},[5368,11817,5649],{"emptyLinePlaceholder":5648},[5368,11819,11820],{"class":5370,"line":10774},[5368,11821,11822],{"class":5374},"# Експеримент\n",[5368,11824,11825,11827,11829,11831,11833,11835,11837],{"class":5370,"line":10780},[5368,11826,5994],{"class":5381},[5368,11828,5998],{"class":5997},[5368,11830,6001],{"class":5560},[5368,11832,6004],{"class":5381},[5368,11834,6007],{"class":5560},[5368,11836,6010],{"class":5997},[5368,11838,5737],{"class":5381},[5368,11840,11841],{"class":5370,"line":10799},[5368,11842,5649],{"emptyLinePlaceholder":5648},[5368,11844,11845],{"class":5370,"line":10804},[5368,11846,11847],{"class":5374},"# Модель 1: Baseline без BN\n",[5368,11849,11850,11853,11856],{"class":5370,"line":10840},[5368,11851,11852],{"class":5381},"torch.manual_seed(",[5368,11854,11855],{"class":5392},"42",[5368,11857,5737],{"class":5381},[5368,11859,11860],{"class":5370,"line":10845},[5368,11861,11862],{"class":5381},"model_baseline = CNNBaseline()\n",[5368,11864,11865],{"class":5370,"line":10850},[5368,11866,11867],{"class":5381},"history_baseline = train_and_evaluate(\n",[5368,11869,11870,11873,11876],{"class":5370,"line":10856},[5368,11871,11872],{"class":5381},"    model_baseline, ",[5368,11874,11875],{"class":5997},"\"Baseline (без BN)\"",[5368,11877,6695],{"class":5381},[5368,11879,11880],{"class":5370,"line":10861},[5368,11881,11882],{"class":5381},"    train_loader, test_loader, \n",[5368,11884,11885,11888,11890,11892,11894,11896,11898,11900,11902,11904],{"class":5370,"line":10890},[5368,11886,11887],{"class":5385},"    epochs",[5368,11889,5846],{"class":5381},[5368,11891,11155],{"class":5392},[5368,11893,5396],{"class":5381},[5368,11895,6033],{"class":5385},[5368,11897,5846],{"class":5381},[5368,11899,6038],{"class":5392},[5368,11901,5396],{"class":5381},[5368,11903,11168],{"class":5385},[5368,11905,11906],{"class":5381},"=device\n",[5368,11908,11909],{"class":5370,"line":10895},[5368,11910,5737],{"class":5381},[5368,11912,11913],{"class":5370,"line":10900},[5368,11914,5649],{"emptyLinePlaceholder":5648},[5368,11916,11917],{"class":5370,"line":10931},[5368,11918,11919],{"class":5374},"# Модель 2: З Batch Normalization\n",[5368,11921,11922,11924,11926],{"class":5370,"line":10962},[5368,11923,11852],{"class":5381},[5368,11925,11855],{"class":5392},[5368,11927,5737],{"class":5381},[5368,11929,11930],{"class":5370,"line":10967},[5368,11931,11932],{"class":5381},"model_bn = CNNWithBN()\n",[5368,11934,11935],{"class":5370,"line":10997},[5368,11936,11937],{"class":5381},"history_bn = train_and_evaluate(\n",[5368,11939,11940,11943,11946],{"class":5370,"line":11027},[5368,11941,11942],{"class":5381},"    model_bn, ",[5368,11944,11945],{"class":5997},"\"CNN + BatchNorm\"",[5368,11947,6695],{"class":5381},[5368,11949,11950],{"class":5370,"line":11032},[5368,11951,11882],{"class":5381},[5368,11953,11954,11956,11958,11960,11962,11964,11966,11968,11971],{"class":5370,"line":11044},[5368,11955,11887],{"class":5385},[5368,11957,5846],{"class":5381},[5368,11959,11155],{"class":5392},[5368,11961,5396],{"class":5381},[5368,11963,6033],{"class":5385},[5368,11965,5846],{"class":5381},[5368,11967,9800],{"class":5392},[5368,11969,11970],{"class":5381},",  ",[5368,11972,11973],{"class":5374},"# ← ЗБІЛЬШЕНИЙ LR у 10 разів!\n",[5368,11975,11976,11979],{"class":5370,"line":11070},[5368,11977,11978],{"class":5385},"    device",[5368,11980,11906],{"class":5381},[5368,11982,11984],{"class":5370,"line":11983},100,[5368,11985,5737],{"class":5381},[5368,11987,11989],{"class":5370,"line":11988},101,[5368,11990,5649],{"emptyLinePlaceholder":5648},[5368,11992,11994,11996,11998,12000,12002,12005],{"class":5370,"line":11993},102,[5368,11995,6358],{"class":5689},[5368,11997,5669],{"class":5381},[5368,11999,6411],{"class":5997},[5368,12001,8223],{"class":8222},[5368,12003,12004],{"class":5997},"🎉 Експеримент завершено!\"",[5368,12006,5737],{"class":5381},[6478,12008,12009,12015,12036,12041,12065],{"v-slot:output":5363},[5191,12010,12011,12012],{},"🚀 ",[5195,12013,12014],{},"Навчання моделі: Baseline (без BN)",[5247,12016,12017,12020,12023,12026,12029],{},[5250,12018,12019],{},"Learning rate: 0.01",[5250,12021,12022],{},"Епоха 5\u002F20: Train Acc=54.23%, Test Acc=52.14%, Time=24.2s",[5250,12024,12025],{},"Епоха 10\u002F20: Train Acc=68.45%, Test Acc=64.78%, Time=24.1s",[5250,12027,12028],{},"Епоха 15\u002F20: Train Acc=76.82%, Test Acc=69.34%, Time=24.3s",[5250,12030,12031,12032,12035],{},"Епоха 20\u002F20: Train Acc=82.15%, Test Acc=",[5195,12033,12034],{},"71.52%",", Time=24.2s",[5191,12037,12011,12038],{},[5195,12039,12040],{},"Навчання моделі: CNN + BatchNorm",[5247,12042,12043,12049,12052,12055,12058],{},[5250,12044,12045,12046,12048],{},"Learning rate: ",[5195,12047,9800],{}," (у 10 разів більший!)",[5250,12050,12051],{},"Епоха 5\u002F20: Train Acc=72.45%, Test Acc=69.82%, Time=26.8s",[5250,12053,12054],{},"Епоха 10\u002F20: Train Acc=84.67%, Test Acc=78.23%, Time=26.7s",[5250,12056,12057],{},"Епоха 15\u002F20: Train Acc=91.23%, Test Acc=82.45%, Time=26.9s",[5250,12059,12060,12061,12064],{},"Епоха 20\u002F20: Train Acc=94.78%, Test Acc=",[5195,12062,12063],{},"84.67%",", Time=26.8s",[5191,12066,12067,12068],{},"🎉 ",[5195,12069,12070],{},"Експеримент завершено!",[5537,12072,12074,12964],{"execution-count":7680,"execution-time":12073},"1.5s",[5358,12075,12077],{"className":5360,"code":12076,"language":5362,"meta":5363,"style":5363},"import matplotlib.pyplot as plt\n\nfig, axes = plt.subplots(1, 2, figsize=(16, 6))\n\n# Графік 1: Test Accuracy\nax1 = axes[0]\nax1.plot(range(1, 21), history_baseline['test_acc'], \n         marker='o', linewidth=2.5, label='Baseline (LR=0.01)', color='#ef4444')\nax1.plot(range(1, 21), history_bn['test_acc'], \n         marker='s', linewidth=2.5, label='+ BatchNorm (LR=0.1)', color='#22c55e')\nax1.set_xlabel('Епоха', fontsize=13)\nax1.set_ylabel('Test Accuracy (%)', fontsize=13)\nax1.set_title('Точність на тестовому датасеті', fontsize=15, fontweight='bold')\nax1.legend(fontsize=12)\nax1.grid(alpha=0.3)\nax1.set_ylim([40, 90])\n\n# Графік 2: Train Loss\nax2 = axes[1]\nax2.plot(range(1, 21), history_baseline['train_loss'], \n         marker='o', linewidth=2.5, label='Baseline', color='#ef4444')\nax2.plot(range(1, 21), history_bn['train_loss'], \n         marker='s', linewidth=2.5, label='+ BatchNorm', color='#22c55e')\nax2.set_xlabel('Епоха', fontsize=13)\nax2.set_ylabel('Train Loss', fontsize=13)\nax2.set_title('Динаміка втрат під час навчання', fontsize=15, fontweight='bold')\nax2.legend(fontsize=12)\nax2.grid(alpha=0.3)\n\nplt.tight_layout()\nplt.show()\n\n# Підсумкова таблиця\nprint(\"\\n📊 Порівняльна таблиця результатів:\\n\")\nprint(f\"{'Модель':\u003C25} | {'LR':\u003C8} | {'Фінал Train Acc':\u003C18} | {'Фінал Test Acc':\u003C18} | {'Приріст':\u003C10}\")\nprint(\"-\" * 95)\nprint(f\"{'Baseline (без BN)':\u003C25} | {0.01:\u003C8.2f} | {history_baseline['train_acc'][-1]:\u003C18.2f} | \"\n      f\"{history_baseline['test_acc'][-1]:\u003C18.2f} | {'—':\u003C10}\")\nprint(f\"{'CNN + BatchNorm':\u003C25} | {0.1:\u003C8.2f} | {history_bn['train_acc'][-1]:\u003C18.2f} | \"\n      f\"{history_bn['test_acc'][-1]:\u003C18.2f} | {'+' + str(round(history_bn['test_acc'][-1] - history_baseline['test_acc'][-1], 2)) + '%':\u003C10}\")\n\nprint(f\"\\n🏆 BatchNorm дозволила:\")\nprint(f\"   ✅ Збільшити LR у 10 разів (0.01 → 0.1)\")\nprint(f\"   ✅ Покращити test accuracy на {history_bn['test_acc'][-1] - history_baseline['test_acc'][-1]:.2f}%\")\nprint(f\"   ✅ Досягти конвергенції швидше (крутіша крива навчання)\")\n",[5365,12078,12079,12089,12093,12118,12122,12127,12135,12158,12196,12217,12254,12272,12289,12315,12327,12339,12354,12358,12363,12371,12391,12426,12446,12481,12497,12514,12539,12551,12563,12567,12571,12575,12579,12584,12603,12665,12681,12729,12763,12807,12879,12883,12900,12913,12951],{"__ignoreMap":5363},[5368,12080,12081,12083,12085,12087],{"class":5370,"line":5371},[5368,12082,5561],{"class":5560},[5368,12084,5624],{"class":5381},[5368,12086,5574],{"class":5560},[5368,12088,5629],{"class":5381},[5368,12090,12091],{"class":5370,"line":5378},[5368,12092,5649],{"emptyLinePlaceholder":5648},[5368,12094,12095,12097,12099,12101,12103,12105,12107,12109,12111,12113,12116],{"class":5370,"line":5410},[5368,12096,6574],{"class":5381},[5368,12098,5549],{"class":5392},[5368,12100,5396],{"class":5381},[5368,12102,6558],{"class":5392},[5368,12104,5396],{"class":5381},[5368,12106,6585],{"class":5385},[5368,12108,6588],{"class":5381},[5368,12110,6591],{"class":5392},[5368,12112,5396],{"class":5381},[5368,12114,12115],{"class":5392},"6",[5368,12117,6599],{"class":5381},[5368,12119,12120],{"class":5370,"line":5592},[5368,12121,5649],{"emptyLinePlaceholder":5648},[5368,12123,12124],{"class":5370,"line":5606},[5368,12125,12126],{"class":5374},"# Графік 1: Test Accuracy\n",[5368,12128,12129,12131,12133],{"class":5370,"line":5619},[5368,12130,6613],{"class":5381},[5368,12132,5860],{"class":5392},[5368,12134,6618],{"class":5381},[5368,12136,12137,12139,12141,12143,12145,12147,12150,12153,12155],{"class":5370,"line":5632},[5368,12138,6623],{"class":5381},[5368,12140,6626],{"class":5689},[5368,12142,5669],{"class":5381},[5368,12144,5549],{"class":5392},[5368,12146,5396],{"class":5381},[5368,12148,12149],{"class":5392},"21",[5368,12151,12152],{"class":5381},"), history_baseline[",[5368,12154,11261],{"class":5997},[5368,12156,12157],{"class":5381},"], \n",[5368,12159,12160,12163,12165,12168,12170,12172,12174,12177,12179,12181,12183,12186,12188,12190,12192,12194],{"class":5370,"line":5645},[5368,12161,12162],{"class":5385},"         marker",[5368,12164,5846],{"class":5381},[5368,12166,12167],{"class":5997},"'o'",[5368,12169,5396],{"class":5381},[5368,12171,6648],{"class":5385},[5368,12173,5846],{"class":5381},[5368,12175,12176],{"class":5392},"2.5",[5368,12178,5396],{"class":5381},[5368,12180,6657],{"class":5385},[5368,12182,5846],{"class":5381},[5368,12184,12185],{"class":5997},"'Baseline (LR=0.01)'",[5368,12187,5396],{"class":5381},[5368,12189,6677],{"class":5385},[5368,12191,5846],{"class":5381},[5368,12193,6916],{"class":5997},[5368,12195,5737],{"class":5381},[5368,12197,12198,12200,12202,12204,12206,12208,12210,12213,12215],{"class":5370,"line":5652},[5368,12199,6623],{"class":5381},[5368,12201,6626],{"class":5689},[5368,12203,5669],{"class":5381},[5368,12205,5549],{"class":5392},[5368,12207,5396],{"class":5381},[5368,12209,12149],{"class":5392},[5368,12211,12212],{"class":5381},"), history_bn[",[5368,12214,11261],{"class":5997},[5368,12216,12157],{"class":5381},[5368,12218,12219,12221,12223,12226,12228,12230,12232,12234,12236,12238,12240,12243,12245,12247,12249,12252],{"class":5370,"line":5658},[5368,12220,12162],{"class":5385},[5368,12222,5846],{"class":5381},[5368,12224,12225],{"class":5997},"'s'",[5368,12227,5396],{"class":5381},[5368,12229,6648],{"class":5385},[5368,12231,5846],{"class":5381},[5368,12233,12176],{"class":5392},[5368,12235,5396],{"class":5381},[5368,12237,6657],{"class":5385},[5368,12239,5846],{"class":5381},[5368,12241,12242],{"class":5997},"'+ BatchNorm (LR=0.1)'",[5368,12244,5396],{"class":5381},[5368,12246,6677],{"class":5385},[5368,12248,5846],{"class":5381},[5368,12250,12251],{"class":5997},"'#22c55e'",[5368,12253,5737],{"class":5381},[5368,12255,12256,12258,12261,12263,12265,12267,12270],{"class":5370,"line":5683},[5368,12257,6781],{"class":5381},[5368,12259,12260],{"class":5997},"'Епоха'",[5368,12262,5396],{"class":5381},[5368,12264,6789],{"class":5385},[5368,12266,5846],{"class":5381},[5368,12268,12269],{"class":5392},"13",[5368,12271,5737],{"class":5381},[5368,12273,12274,12276,12279,12281,12283,12285,12287],{"class":5370,"line":5700},[5368,12275,6801],{"class":5381},[5368,12277,12278],{"class":5997},"'Test Accuracy (%)'",[5368,12280,5396],{"class":5381},[5368,12282,6789],{"class":5385},[5368,12284,5846],{"class":5381},[5368,12286,12269],{"class":5392},[5368,12288,5737],{"class":5381},[5368,12290,12291,12293,12296,12298,12300,12302,12305,12307,12309,12311,12313],{"class":5370,"line":5720},[5368,12292,6819],{"class":5381},[5368,12294,12295],{"class":5997},"'Точність на тестовому датасеті'",[5368,12297,5396],{"class":5381},[5368,12299,6789],{"class":5385},[5368,12301,5846],{"class":5381},[5368,12303,12304],{"class":5392},"15",[5368,12306,5396],{"class":5381},[5368,12308,6839],{"class":5385},[5368,12310,5846],{"class":5381},[5368,12312,6844],{"class":5997},[5368,12314,5737],{"class":5381},[5368,12316,12317,12319,12321,12323,12325],{"class":5370,"line":5740},[5368,12318,6851],{"class":5381},[5368,12320,6789],{"class":5385},[5368,12322,5846],{"class":5381},[5368,12324,6794],{"class":5392},[5368,12326,5737],{"class":5381},[5368,12328,12329,12331,12333,12335,12337],{"class":5370,"line":5756},[5368,12330,6865],{"class":5381},[5368,12332,6868],{"class":5385},[5368,12334,5846],{"class":5381},[5368,12336,6873],{"class":5392},[5368,12338,5737],{"class":5381},[5368,12340,12341,12344,12347,12349,12352],{"class":5370,"line":5776},[5368,12342,12343],{"class":5381},"ax1.set_ylim([",[5368,12345,12346],{"class":5392},"40",[5368,12348,5396],{"class":5381},[5368,12350,12351],{"class":5392},"90",[5368,12353,5431],{"class":5381},[5368,12355,12356],{"class":5370,"line":5793},[5368,12357,5649],{"emptyLinePlaceholder":5648},[5368,12359,12360],{"class":5370,"line":5810},[5368,12361,12362],{"class":5374},"# Графік 2: Train Loss\n",[5368,12364,12365,12367,12369],{"class":5370,"line":5818},[5368,12366,6889],{"class":5381},[5368,12368,5549],{"class":5392},[5368,12370,6618],{"class":5381},[5368,12372,12373,12375,12377,12379,12381,12383,12385,12387,12389],{"class":5370,"line":5824},[5368,12374,6898],{"class":5381},[5368,12376,6626],{"class":5689},[5368,12378,5669],{"class":5381},[5368,12380,5549],{"class":5392},[5368,12382,5396],{"class":5381},[5368,12384,12149],{"class":5392},[5368,12386,12152],{"class":5381},[5368,12388,11641],{"class":5997},[5368,12390,12157],{"class":5381},[5368,12392,12393,12395,12397,12399,12401,12403,12405,12407,12409,12411,12413,12416,12418,12420,12422,12424],{"class":5370,"line":5854},[5368,12394,12162],{"class":5385},[5368,12396,5846],{"class":5381},[5368,12398,12167],{"class":5997},[5368,12400,5396],{"class":5381},[5368,12402,6648],{"class":5385},[5368,12404,5846],{"class":5381},[5368,12406,12176],{"class":5392},[5368,12408,5396],{"class":5381},[5368,12410,6657],{"class":5385},[5368,12412,5846],{"class":5381},[5368,12414,12415],{"class":5997},"'Baseline'",[5368,12417,5396],{"class":5381},[5368,12419,6677],{"class":5385},[5368,12421,5846],{"class":5381},[5368,12423,6916],{"class":5997},[5368,12425,5737],{"class":5381},[5368,12427,12428,12430,12432,12434,12436,12438,12440,12442,12444],{"class":5370,"line":5870},[5368,12429,6898],{"class":5381},[5368,12431,6626],{"class":5689},[5368,12433,5669],{"class":5381},[5368,12435,5549],{"class":5392},[5368,12437,5396],{"class":5381},[5368,12439,12149],{"class":5392},[5368,12441,12212],{"class":5381},[5368,12443,11641],{"class":5997},[5368,12445,12157],{"class":5381},[5368,12447,12448,12450,12452,12454,12456,12458,12460,12462,12464,12466,12468,12471,12473,12475,12477,12479],{"class":5370,"line":5886},[5368,12449,12162],{"class":5385},[5368,12451,5846],{"class":5381},[5368,12453,12225],{"class":5997},[5368,12455,5396],{"class":5381},[5368,12457,6648],{"class":5385},[5368,12459,5846],{"class":5381},[5368,12461,12176],{"class":5392},[5368,12463,5396],{"class":5381},[5368,12465,6657],{"class":5385},[5368,12467,5846],{"class":5381},[5368,12469,12470],{"class":5997},"'+ BatchNorm'",[5368,12472,5396],{"class":5381},[5368,12474,6677],{"class":5385},[5368,12476,5846],{"class":5381},[5368,12478,12251],{"class":5997},[5368,12480,5737],{"class":5381},[5368,12482,12483,12485,12487,12489,12491,12493,12495],{"class":5370,"line":5900},[5368,12484,7041],{"class":5381},[5368,12486,12260],{"class":5997},[5368,12488,5396],{"class":5381},[5368,12490,6789],{"class":5385},[5368,12492,5846],{"class":5381},[5368,12494,12269],{"class":5392},[5368,12496,5737],{"class":5381},[5368,12498,12499,12501,12504,12506,12508,12510,12512],{"class":5370,"line":5909},[5368,12500,7058],{"class":5381},[5368,12502,12503],{"class":5997},"'Train Loss'",[5368,12505,5396],{"class":5381},[5368,12507,6789],{"class":5385},[5368,12509,5846],{"class":5381},[5368,12511,12269],{"class":5392},[5368,12513,5737],{"class":5381},[5368,12515,12516,12518,12521,12523,12525,12527,12529,12531,12533,12535,12537],{"class":5370,"line":5923},[5368,12517,7076],{"class":5381},[5368,12519,12520],{"class":5997},"'Динаміка втрат під час навчання'",[5368,12522,5396],{"class":5381},[5368,12524,6789],{"class":5385},[5368,12526,5846],{"class":5381},[5368,12528,12304],{"class":5392},[5368,12530,5396],{"class":5381},[5368,12532,6839],{"class":5385},[5368,12534,5846],{"class":5381},[5368,12536,6844],{"class":5997},[5368,12538,5737],{"class":5381},[5368,12540,12541,12543,12545,12547,12549],{"class":5370,"line":5937},[5368,12542,7104],{"class":5381},[5368,12544,6789],{"class":5385},[5368,12546,5846],{"class":5381},[5368,12548,6794],{"class":5392},[5368,12550,5737],{"class":5381},[5368,12552,12553,12555,12557,12559,12561],{"class":5370,"line":5947},[5368,12554,7117],{"class":5381},[5368,12556,6868],{"class":5385},[5368,12558,5846],{"class":5381},[5368,12560,6873],{"class":5392},[5368,12562,5737],{"class":5381},[5368,12564,12565],{"class":5370,"line":5953},[5368,12566,5649],{"emptyLinePlaceholder":5648},[5368,12568,12569],{"class":5370,"line":5962},[5368,12570,7134],{"class":5381},[5368,12572,12573],{"class":5370,"line":5971},[5368,12574,7139],{"class":5381},[5368,12576,12577],{"class":5370,"line":5980},[5368,12578,5649],{"emptyLinePlaceholder":5648},[5368,12580,12581],{"class":5370,"line":5985},[5368,12582,12583],{"class":5374},"# Підсумкова таблиця\n",[5368,12585,12586,12588,12590,12592,12594,12597,12599,12601],{"class":5370,"line":5991},[5368,12587,6358],{"class":5689},[5368,12589,5669],{"class":5381},[5368,12591,6411],{"class":5997},[5368,12593,8223],{"class":8222},[5368,12595,12596],{"class":5997},"📊 Порівняльна таблиця результатів:",[5368,12598,8223],{"class":8222},[5368,12600,6411],{"class":5997},[5368,12602,5737],{"class":5381},[5368,12604,12605,12607,12609,12611,12613,12615,12618,12621,12624,12626,12629,12632,12634,12636,12639,12642,12644,12646,12649,12651,12653,12655,12658,12661,12663],{"class":5370,"line":6015},[5368,12606,6358],{"class":5689},[5368,12608,5669],{"class":5381},[5368,12610,6363],{"class":5661},[5368,12612,6411],{"class":5997},[5368,12614,6369],{"class":5661},[5368,12616,12617],{"class":5997},"'Модель'",[5368,12619,12620],{"class":5661},":\u003C25}",[5368,12622,12623],{"class":5997}," | ",[5368,12625,6369],{"class":5661},[5368,12627,12628],{"class":5997},"'LR'",[5368,12630,12631],{"class":5661},":\u003C8}",[5368,12633,12623],{"class":5997},[5368,12635,6369],{"class":5661},[5368,12637,12638],{"class":5997},"'Фінал Train Acc'",[5368,12640,12641],{"class":5661},":\u003C18}",[5368,12643,12623],{"class":5997},[5368,12645,6369],{"class":5661},[5368,12647,12648],{"class":5997},"'Фінал Test Acc'",[5368,12650,12641],{"class":5661},[5368,12652,12623],{"class":5997},[5368,12654,6369],{"class":5661},[5368,12656,12657],{"class":5997},"'Приріст'",[5368,12659,12660],{"class":5661},":\u003C10}",[5368,12662,6411],{"class":5997},[5368,12664,5737],{"class":5381},[5368,12666,12667,12669,12671,12674,12676,12679],{"class":5370,"line":6021},[5368,12668,6358],{"class":5689},[5368,12670,5669],{"class":5381},[5368,12672,12673],{"class":5997},"\"-\"",[5368,12675,9454],{"class":5381},[5368,12677,12678],{"class":5392},"95",[5368,12680,5737],{"class":5381},[5368,12682,12683,12685,12687,12689,12691,12693,12696,12698,12700,12702,12704,12707,12709,12711,12714,12716,12719,12721,12723,12726],{"class":5370,"line":6027},[5368,12684,6358],{"class":5689},[5368,12686,5669],{"class":5381},[5368,12688,6363],{"class":5661},[5368,12690,6411],{"class":5997},[5368,12692,6369],{"class":5661},[5368,12694,12695],{"class":5997},"'Baseline (без BN)'",[5368,12697,12620],{"class":5661},[5368,12699,12623],{"class":5997},[5368,12701,6369],{"class":5661},[5368,12703,6038],{"class":5392},[5368,12705,12706],{"class":5661},":\u003C8.2f}",[5368,12708,12623],{"class":5997},[5368,12710,6369],{"class":5661},[5368,12712,12713],{"class":5381},"history_baseline[",[5368,12715,11248],{"class":5997},[5368,12717,12718],{"class":5381},"][-",[5368,12720,5549],{"class":5392},[5368,12722,6405],{"class":5381},[5368,12724,12725],{"class":5661},":\u003C18.2f}",[5368,12727,12728],{"class":5997}," | \"\n",[5368,12730,12731,12734,12736,12738,12740,12742,12744,12746,12748,12750,12752,12754,12757,12759,12761],{"class":5370,"line":6053},[5368,12732,12733],{"class":5661},"      f",[5368,12735,6411],{"class":5997},[5368,12737,6369],{"class":5661},[5368,12739,12713],{"class":5381},[5368,12741,11261],{"class":5997},[5368,12743,12718],{"class":5381},[5368,12745,5549],{"class":5392},[5368,12747,6405],{"class":5381},[5368,12749,12725],{"class":5661},[5368,12751,12623],{"class":5997},[5368,12753,6369],{"class":5661},[5368,12755,12756],{"class":5997},"'—'",[5368,12758,12660],{"class":5661},[5368,12760,6411],{"class":5997},[5368,12762,5737],{"class":5381},[5368,12764,12765,12767,12769,12771,12773,12775,12778,12780,12782,12784,12786,12788,12790,12792,12795,12797,12799,12801,12803,12805],{"class":5370,"line":6058},[5368,12766,6358],{"class":5689},[5368,12768,5669],{"class":5381},[5368,12770,6363],{"class":5661},[5368,12772,6411],{"class":5997},[5368,12774,6369],{"class":5661},[5368,12776,12777],{"class":5997},"'CNN + BatchNorm'",[5368,12779,12620],{"class":5661},[5368,12781,12623],{"class":5997},[5368,12783,6369],{"class":5661},[5368,12785,9800],{"class":5392},[5368,12787,12706],{"class":5661},[5368,12789,12623],{"class":5997},[5368,12791,6369],{"class":5661},[5368,12793,12794],{"class":5381},"history_bn[",[5368,12796,11248],{"class":5997},[5368,12798,12718],{"class":5381},[5368,12800,5549],{"class":5392},[5368,12802,6405],{"class":5381},[5368,12804,12725],{"class":5661},[5368,12806,12728],{"class":5997},[5368,12808,12809,12811,12813,12815,12817,12819,12821,12823,12825,12827,12829,12831,12834,12837,12840,12842,12845,12848,12850,12852,12854,12857,12859,12861,12863,12865,12867,12870,12873,12875,12877],{"class":5370,"line":6064},[5368,12810,12733],{"class":5661},[5368,12812,6411],{"class":5997},[5368,12814,6369],{"class":5661},[5368,12816,12794],{"class":5381},[5368,12818,11261],{"class":5997},[5368,12820,12718],{"class":5381},[5368,12822,5549],{"class":5392},[5368,12824,6405],{"class":5381},[5368,12826,12725],{"class":5661},[5368,12828,12623],{"class":5997},[5368,12830,6369],{"class":5661},[5368,12832,12833],{"class":5997},"'+'",[5368,12835,12836],{"class":5381}," + ",[5368,12838,12839],{"class":5665},"str",[5368,12841,5669],{"class":5381},[5368,12843,12844],{"class":5689},"round",[5368,12846,12847],{"class":5381},"(history_bn[",[5368,12849,11261],{"class":5997},[5368,12851,12718],{"class":5381},[5368,12853,5549],{"class":5392},[5368,12855,12856],{"class":5381},"] - history_baseline[",[5368,12858,11261],{"class":5997},[5368,12860,12718],{"class":5381},[5368,12862,5549],{"class":5392},[5368,12864,6674],{"class":5381},[5368,12866,6558],{"class":5392},[5368,12868,12869],{"class":5381},")) + ",[5368,12871,12872],{"class":5997},"'%'",[5368,12874,12660],{"class":5661},[5368,12876,6411],{"class":5997},[5368,12878,5737],{"class":5381},[5368,12880,12881],{"class":5370,"line":6070},[5368,12882,5649],{"emptyLinePlaceholder":5648},[5368,12884,12885,12887,12889,12891,12893,12895,12898],{"class":5370,"line":6076},[5368,12886,6358],{"class":5689},[5368,12888,5669],{"class":5381},[5368,12890,6363],{"class":5661},[5368,12892,6411],{"class":5997},[5368,12894,8223],{"class":8222},[5368,12896,12897],{"class":5997},"🏆 BatchNorm дозволила:\"",[5368,12899,5737],{"class":5381},[5368,12901,12902,12904,12906,12908,12911],{"class":5370,"line":6094},[5368,12903,6358],{"class":5689},[5368,12905,5669],{"class":5381},[5368,12907,6363],{"class":5661},[5368,12909,12910],{"class":5997},"\"   ✅ Збільшити LR у 10 разів (0.01 → 0.1)\"",[5368,12912,5737],{"class":5381},[5368,12914,12915,12917,12919,12921,12924,12926,12928,12930,12932,12934,12936,12938,12940,12942,12944,12946,12949],{"class":5370,"line":6099},[5368,12916,6358],{"class":5689},[5368,12918,5669],{"class":5381},[5368,12920,6363],{"class":5661},[5368,12922,12923],{"class":5997},"\"   ✅ Покращити test accuracy на ",[5368,12925,6369],{"class":5661},[5368,12927,12794],{"class":5381},[5368,12929,11261],{"class":5997},[5368,12931,12718],{"class":5381},[5368,12933,5549],{"class":5392},[5368,12935,12856],{"class":5381},[5368,12937,11261],{"class":5997},[5368,12939,12718],{"class":5381},[5368,12941,5549],{"class":5392},[5368,12943,6405],{"class":5381},[5368,12945,11768],{"class":5661},[5368,12947,12948],{"class":5997},"%\"",[5368,12950,5737],{"class":5381},[5368,12952,12953,12955,12957,12959,12962],{"class":5370,"line":6135},[5368,12954,6358],{"class":5689},[5368,12956,5669],{"class":5381},[5368,12958,6363],{"class":5661},[5368,12960,12961],{"class":5997},"\"   ✅ Досягти конвергенції швидше (крутіша крива навчання)\"",[5368,12963,5737],{"class":5381},[6478,12965,12966,12973,12978,13040,13046],{"v-slot:output":5363},[5191,12967,12968],{},[7143,12969],{"alt":12970,"className":12971,"src":12972},"Batch Normalization: значне покращення точності та стабільності навчання",[7147],"\u002Fimages\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fbatch-normalization\u002F02.png",[5191,12974,8594,12975],{},[5195,12976,12977],{},"Порівняльна таблиця результатів:",[6487,12979,12980,12999],{},[6490,12981,12982],{},[6493,12983,12984,12987,12990,12993,12996],{},[6496,12985,12986],{"align":6498},"Модель",[6496,12988,12989],{"align":6498},"LR",[6496,12991,12992],{"align":6498},"Фінал Train Acc",[6496,12994,12995],{"align":6498},"Фінал Test Acc",[6496,12997,12998],{"align":6498},"Приріст",[6510,13000,13001,13017],{},[6493,13002,13003,13008,13010,13013,13015],{},[6515,13004,13005],{"align":6498},[5195,13006,13007],{},"Baseline (без BN)",[6515,13009,6038],{"align":6498},[6515,13011,13012],{"align":6498},"82.15%",[6515,13014,12034],{"align":6498},[6515,13016,9771],{"align":6498},[6493,13018,13019,13023,13028,13031,13035],{},[6515,13020,13021],{"align":6498},[5195,13022,9912],{},[6515,13024,13025],{"align":6498},[5195,13026,13027],{},"0.10",[6515,13029,13030],{"align":6498},"94.78%",[6515,13032,13033],{"align":6498},[5195,13034,12063],{},[6515,13036,13037],{"align":6498},[5195,13038,13039],{},"+13.15%",[5191,13041,13042,13043],{},"🏆 ",[5195,13044,13045],{},"BatchNorm дозволила:",[5247,13047,13048,13055,13061,13068],{},[5250,13049,13050,13051,13054],{},"✅ Збільшити LR у ",[5195,13052,13053],{},"10 разів"," (0.01 → 0.1)",[5250,13056,13057,13058],{},"✅ Покращити test accuracy на ",[5195,13059,13060],{},"13.15%",[5250,13062,13063,13064,13067],{},"✅ Досягти конвергенції ",[5195,13065,13066],{},"швидше"," (крутіша крива навчання)",[5250,13069,13070],{},"✅ Зменшити gap між train та test (менше перенавчання)",[5210,13072,13073,13085,13093,13097],{},[5213,13074,13076,13077,13080,13081,13084],{"icon":92,"title":13075},"⚡ Швидша конвергенція","З BN модель досягла 70% test accuracy за ",[5195,13078,13079],{},"5 епох",", тоді як baseline — лише за 15 епох. Прискорення у ",[5195,13082,13083],{},"3 рази","!",[5213,13086,13089,13090,13092],{"icon":13087,"title":13088},"i-lucide-trending-up","📈 Вища фінальна точність","84.67% vs 71.52% — приріст ",[5195,13091,13060],{},". Це величезна різниця для однієї техніки!",[5213,13094,13096],{"icon":5223,"title":13095},"🎯 Менше перенавчання","Gap між train та test accuracy: BN = 10.11% vs Baseline = 10.63%. BN діє як регуляризація.",[5213,13098,13100],{"icon":3072,"title":13099},"🔧 Стабільність навчання","З BN можна використовувати LR=0.1 без нестабільності. Baseline з LR=0.1 розбігається (NaN після кількох епох).",[5304,13102],{},[5186,13104,13106],{"id":13105},"обмеження-та-альтернативи-batch-normalization","Обмеження та альтернативи Batch Normalization",[5191,13108,13109],{},"Попри всі переваги, Batch Normalization має кілька обмежень, які призвели до розробки альтернативних методів нормалізації.",[5210,13111,13112,13138,13158,13180],{},[5213,13113,13116,13126,13132],{"icon":13114,"title":13115},"i-lucide-users","⚠️ Залежність від розміру батчу",[5191,13117,13118,13121,13122,13125],{},[5195,13119,13120],{},"Проблема:"," Статистика μ та σ² обчислюється по батчу. Якщо ",[5195,13123,13124],{},"batch_size \u003C 16",", статистика стає дуже шумною, і BN працює погано.",[5191,13127,13128,13131],{},[5195,13129,13130],{},"Випадки:"," Обмеження GPU пам'яті (великі зображення 512×512), відео (3D convolutions), рекурентні мережі з довгими послідовностями.",[5191,13133,13134,13137],{},[5195,13135,13136],{},"Рішення:"," Group Normalization або Layer Normalization (не залежать від batch size).",[5213,13139,13141,13150],{"icon":2536,"title":13140},"⚠️ Не працює для RNN\u002FLSTM",[5191,13142,13143,13145,13146,13149],{},[5195,13144,13120],{}," У рекурентних мережах послідовності мають ",[5195,13147,13148],{},"різну довжину",". Неможливо обчислити μ та σ² по батчу, коли у одного прикладу 10 токенів, а у іншого — 50.",[5191,13151,13152,5489,13154,13157],{},[5195,13153,13136],{},[5195,13155,13156],{},"Layer Normalization"," — нормалізація по features замість по батчу. Використовується у Transformers (BERT, GPT).",[5213,13159,13161,13166,13171],{"icon":255,"title":13160},"⚠️ Додаткові обчислення",[5191,13162,13163,13165],{},[5195,13164,13120],{}," BN додає 10-15% overhead до часу forward\u002Fbackward pass.",[5191,13167,13168,13170],{},[5195,13169,13130],{}," Якщо швидкість inference критична (edge devices, реальний час).",[5191,13172,13173,13175,13176,13179],{},[5195,13174,13136],{}," Після навчання можна ",[5195,13177,13178],{},"fuse BN з попереднім Conv\u002FLinear шаром"," (обчислити еквівалентні ваги без окремого BN).",[5213,13181,13183,13188,13194],{"icon":4590,"title":13182},"⚠️ Проблеми з Transfer Learning",[5191,13184,13185,13187],{},[5195,13186,13120],{}," Running statistics обчислені на одному датасеті можуть не підходити для іншого.",[5191,13189,13190,13193],{},[5195,13191,13192],{},"Приклад:"," Pretrained ImageNet модель має running stats для природних зображень. При fine-tuning на медичні рентгени розподіл активацій інший.",[5191,13195,13196,13198],{},[5195,13197,13136],{}," Re-compute running stats на новому датасеті або freeze BN шари.",[5322,13200,13202],{"id":13201},"альтернативні-методи-нормалізації","Альтернативні методи нормалізації",[6487,13204,13205,13218],{},[6490,13206,13207],{},[6493,13208,13209,13212,13215],{},[6496,13210,13211],{"align":6498},"Метод",[6496,13213,13214],{"align":6498},"Нормалізація по",[6496,13216,13217],{"align":6498},"Застосування",[6510,13219,13220,13233,13246,13259],{},[6493,13221,13222,13227,13230],{},[6515,13223,13224],{"align":6498},[5195,13225,13226],{},"Batch Norm",[6515,13228,13229],{"align":6498},"Батчу та просторових координатах",[6515,13231,13232],{"align":6498},"CNN для зображень (batch_size ≥ 32)",[6493,13234,13235,13240,13243],{},[6515,13236,13237],{"align":6498},[5195,13238,13239],{},"Layer Norm",[6515,13241,13242],{"align":6498},"Features (всередині одного прикладу)",[6515,13244,13245],{"align":6498},"Transformers, RNN, NLP",[6493,13247,13248,13253,13256],{},[6515,13249,13250],{"align":6498},[5195,13251,13252],{},"Instance Norm",[6515,13254,13255],{"align":6498},"Просторових координатах кожного прикладу окремо",[6515,13257,13258],{"align":6498},"Style transfer, GAN",[6493,13260,13261,13266,13269],{},[6515,13262,13263],{"align":6498},[5195,13264,13265],{},"Group Norm",[6515,13267,13268],{"align":6498},"Групах каналів",[6515,13270,13271],{"align":6498},"CNN з малими батчами (2-8)",[7507,13273,13274,13279,13312],{},[5191,13275,13276],{},[5195,13277,13278],{},"Загальна рекомендація:",[5247,13280,13281,13289,13296,13304],{},[5250,13282,13283,5489,13286],{},[5195,13284,13285],{},"CNN для зображень (batch ≥ 32):",[5195,13287,13288],{},"Batch Normalization",[5250,13290,13291,5489,13294],{},[5195,13292,13293],{},"Transformers \u002F NLP:",[5195,13295,13156],{},[5250,13297,13298,5489,13301],{},[5195,13299,13300],{},"Style Transfer \u002F GAN:",[5195,13302,13303],{},"Instance Normalization",[5250,13305,13306,5489,13309],{},[5195,13307,13308],{},"Обмеження пам'яті (batch \u003C 16):",[5195,13310,13311],{},"Group Normalization",[5191,13313,13314,13315,13318],{},"Batch Normalization залишається ",[5195,13316,13317],{},"золотим стандартом"," для більшості задач комп'ютерного зору.",[5304,13320],{},[5186,13322,13324],{"id":13323},"висновки-та-практичні-рекомендації","Висновки та практичні рекомендації",[13326,13327,13328,13357,13379,13484],"accordion",{},[13329,13330,13333,13339,13350],"accordion-item",{"icon":13331,"label":13332},"i-lucide-help-circle","❓ Завжди використовувати Batch Normalization?",[5191,13334,13335,13338],{},[5195,13336,13337],{},"Майже завжди — ТАК"," для CNN. Виключення:",[5247,13340,13341,13344,13347],{},[5250,13342,13343],{},"Дуже малі батчі (\u003C 8) → використайте Group Normalization",[5250,13345,13346],{},"RNN\u002FLSTM → використайте Layer Normalization",[5250,13348,13349],{},"Transfer learning із заморожен!ими шарами → можливо, краще без BN",[5191,13351,13352,13353,13356],{},"Для нових архітектур: ",[5195,13354,13355],{},"почніть з BN",", експериментуйте з альтернативами лише якщо є проблеми.",[13329,13358,13360,13366,13373],{"icon":13331,"label":13359},"❓ Чи потрібен Dropout якщо є Batch Normalization?",[5191,13361,13362,13365],{},[5195,13363,13364],{},"Зазвичай НІ"," або значно менший (p=0.1-0.2 замість 0.5).",[5191,13367,13368,13369,13372],{},"BN вже діє як регуляризація через шум у батч-статистиці. Комбінація BN + Dropout може ",[5195,13370,13371],{},"погіршити"," результати через надмірну регуляризацію.",[5191,13374,13375,13378],{},[5195,13376,13377],{},"Виключення:"," дуже великі датасети (> 1M прикладів) — можна додати легкий Dropout (p=0.2) перед останніми FC шарами.",[13329,13380,13382,13387],{"icon":13331,"label":13381},"❓ Що робити при fine-tuning pretrained моделі?",[5191,13383,13384],{},[5195,13385,13386],{},"Два підходи:",[7158,13388,13389,13445],{},[5250,13390,13391,13394,13395],{},[5195,13392,13393],{},"Freeze BN шари"," (рекомендовано):",[5358,13396,13398],{"className":5360,"code":13397,"language":5362,"meta":5363,"style":5363},"for module in model.modules():\n    if isinstance(module, nn.BatchNorm2d):\n        module.eval()  # Завжди у eval режимі\n        module.weight.requires_grad = False\n        module.bias.requires_grad = False\n",[5365,13399,13400,13412,13422,13430,13438],{"__ignoreMap":5363},[5368,13401,13402,13404,13407,13409],{"class":5370,"line":5371},[5368,13403,6196],{"class":5560},[5368,13405,13406],{"class":5381}," module ",[5368,13408,6202],{"class":5560},[5368,13410,13411],{"class":5381}," model.modules():\n",[5368,13413,13414,13416,13419],{"class":5370,"line":5378},[5368,13415,6214],{"class":5560},[5368,13417,13418],{"class":5689}," isinstance",[5368,13420,13421],{"class":5381},"(module, nn.BatchNorm2d):\n",[5368,13423,13424,13427],{"class":5370,"line":5410},[5368,13425,13426],{"class":5381},"        module.eval()  ",[5368,13428,13429],{"class":5374},"# Завжди у eval режимі\n",[5368,13431,13432,13435],{"class":5370,"line":5592},[5368,13433,13434],{"class":5381},"        module.weight.requires_grad = ",[5368,13436,13437],{"class":5661},"False\n",[5368,13439,13440,13443],{"class":5370,"line":5606},[5368,13441,13442],{"class":5381},"        module.bias.requires_grad = ",[5368,13444,13437],{"class":5661},[5250,13446,13447,13450],{},[5195,13448,13449],{},"Re-compute running stats:",[5358,13451,13453],{"className":5360,"code":13452,"language":5362,"meta":5363,"style":5363},"# Після завантаження pretrained ваг\nmodel.train()\nfor images, _ in new_dataset_loader:\n    model(images)  # Просто forward, без backward\n",[5365,13454,13455,13460,13464,13476],{"__ignoreMap":5363},[5368,13456,13457],{"class":5370,"line":5371},[5368,13458,13459],{"class":5374},"# Після завантаження pretrained ваг\n",[5368,13461,13462],{"class":5370,"line":5378},[5368,13463,6190],{"class":5381},[5368,13465,13466,13468,13471,13473],{"class":5370,"line":5410},[5368,13467,6196],{"class":5560},[5368,13469,13470],{"class":5381}," images, _ ",[5368,13472,6202],{"class":5560},[5368,13474,13475],{"class":5381}," new_dataset_loader:\n",[5368,13477,13478,13481],{"class":5370,"line":5592},[5368,13479,13480],{"class":5381},"    model(images)  ",[5368,13482,13483],{"class":5374},"# Просто forward, без backward\n",[13329,13485,13487,13492,13505,13510],{"icon":13331,"label":13486},"❓ Як дебажити проблеми з Batch Normalization?",[5191,13488,13489],{},[5195,13490,13491],{},"Симптоми проблем:",[5247,13493,13494,13499,13502],{},[5250,13495,13496,13497],{},"Train accuracy зростає, test accuracy — ні → забули ",[5365,13498,8040],{},[5250,13500,13501],{},"Prediction нестабільні (різні при кожному запуску) → використовуєте train mode при inference",[5250,13503,13504],{},"Loss не зменшується → можливо, занадто малий batch_size (\u003C 8)",[5191,13506,13507],{},[5195,13508,13509],{},"Діагностика:",[5358,13511,13513],{"className":5360,"code":13512,"language":5362,"meta":5363,"style":5363},"# Перевірка режиму\nprint(f\"Model training: {model.training}\")\nfor module in model.modules():\n    if isinstance(module, nn.BatchNorm2d):\n        print(f\"BN training: {module.training}\")\n\n# Перевірка running stats\nbn_layer = model.bn1  # приклад\nprint(f\"Running mean: {bn_layer.running_mean[:5]}\")\nprint(f\"Running var: {bn_layer.running_var[:5]}\")\n",[5365,13514,13515,13520,13542,13552,13560,13583,13587,13592,13600,13626],{"__ignoreMap":5363},[5368,13516,13517],{"class":5370,"line":5371},[5368,13518,13519],{"class":5374},"# Перевірка режиму\n",[5368,13521,13522,13524,13526,13528,13531,13533,13536,13538,13540],{"class":5370,"line":5378},[5368,13523,6358],{"class":5689},[5368,13525,5669],{"class":5381},[5368,13527,6363],{"class":5661},[5368,13529,13530],{"class":5997},"\"Model training: ",[5368,13532,6369],{"class":5661},[5368,13534,13535],{"class":5381},"model.training",[5368,13537,6378],{"class":5661},[5368,13539,6411],{"class":5997},[5368,13541,5737],{"class":5381},[5368,13543,13544,13546,13548,13550],{"class":5370,"line":5410},[5368,13545,6196],{"class":5560},[5368,13547,13406],{"class":5381},[5368,13549,6202],{"class":5560},[5368,13551,13411],{"class":5381},[5368,13553,13554,13556,13558],{"class":5370,"line":5592},[5368,13555,6214],{"class":5560},[5368,13557,13418],{"class":5689},[5368,13559,13421],{"class":5381},[5368,13561,13562,13565,13567,13569,13572,13574,13577,13579,13581],{"class":5370,"line":5606},[5368,13563,13564],{"class":5689},"        print",[5368,13566,5669],{"class":5381},[5368,13568,6363],{"class":5661},[5368,13570,13571],{"class":5997},"\"BN training: ",[5368,13573,6369],{"class":5661},[5368,13575,13576],{"class":5381},"module.training",[5368,13578,6378],{"class":5661},[5368,13580,6411],{"class":5997},[5368,13582,5737],{"class":5381},[5368,13584,13585],{"class":5370,"line":5619},[5368,13586,5649],{"emptyLinePlaceholder":5648},[5368,13588,13589],{"class":5370,"line":5632},[5368,13590,13591],{"class":5374},"# Перевірка running stats\n",[5368,13593,13594,13597],{"class":5370,"line":5645},[5368,13595,13596],{"class":5381},"bn_layer = model.bn1  ",[5368,13598,13599],{"class":5374},"# приклад\n",[5368,13601,13602,13604,13606,13608,13611,13613,13616,13618,13620,13622,13624],{"class":5370,"line":5652},[5368,13603,6358],{"class":5689},[5368,13605,5669],{"class":5381},[5368,13607,6363],{"class":5661},[5368,13609,13610],{"class":5997},"\"Running mean: ",[5368,13612,6369],{"class":5661},[5368,13614,13615],{"class":5381},"bn_layer.running_mean[:",[5368,13617,6596],{"class":5392},[5368,13619,6405],{"class":5381},[5368,13621,6378],{"class":5661},[5368,13623,6411],{"class":5997},[5368,13625,5737],{"class":5381},[5368,13627,13628,13630,13632,13634,13637,13639,13642,13644,13646,13648,13650],{"class":5370,"line":5658},[5368,13629,6358],{"class":5689},[5368,13631,5669],{"class":5381},[5368,13633,6363],{"class":5661},[5368,13635,13636],{"class":5997},"\"Running var: ",[5368,13638,6369],{"class":5661},[5368,13640,13641],{"class":5381},"bn_layer.running_var[:",[5368,13643,6596],{"class":5392},[5368,13645,6405],{"class":5381},[5368,13647,6378],{"class":5661},[5368,13649,6411],{"class":5997},[5368,13651,5737],{"class":5381},[7625,13653,13654,13659,13679],{},[5191,13655,13656],{},[5195,13657,13658],{},"Золоті правила Batch Normalization:",[7158,13660,13661,13664,13670,13673,13676],{},[5250,13662,13663],{},"Розміщувати після Conv\u002FLinear, перед Activation",[5250,13665,13666,13667,13669],{},"Завжди ",[5365,13668,8040],{}," перед тестуванням\u002Finference",[5250,13671,13672],{},"Використовувати batch_size ≥ 32 для стабільної статистики",[5250,13674,13675],{},"Зменшити або прибрати Dropout при використанні BN",[5250,13677,13678],{},"Можна збільшити learning rate у 5-10 разів порівняно з baseline",[5191,13680,13681],{},"Ці правила працюють у 95% випадків!",[5304,13683],{},[5191,13685,13686,13687,13689],{},"У наступній статті ми розглянемо ",[5195,13688,3968],{}," — як поєднати BN, Dropout, weight decay та data augmentation для максимальної генералізації.",[13691,13692,13693],"style",{},"html pre.shiki code .spJ8K, html code.shiki .spJ8K{--shiki-light:#008000;--shiki-default:#6A9955;--shiki-dark:#6A9955}html pre.shiki code .sHH4Y, html code.shiki .sHH4Y{--shiki-light:#000000;--shiki-default:#D4D4D4;--shiki-dark:#D4D4D4}html pre.shiki code .siwwj, html code.shiki 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.sjcCO{--shiki-light:#EE0000;--shiki-default:#D7BA7D;--shiki-dark:#D7BA7D}",{"title":5363,"searchDepth":5378,"depth":5378,"links":13695},[13696,13697,13705,13708,13709,13714,13718,13721,13722,13725],{"id":5188,"depth":5378,"text":5189},{"id":5308,"depth":5378,"text":5309,"children":13698},[13699,13700,13701,13702,13703,13704],{"id":5324,"depth":5410,"text":5325},{"id":5441,"depth":5410,"text":5442},{"id":5467,"depth":5410,"text":5468},{"id":5481,"depth":5410,"text":5482},{"id":5500,"depth":5410,"text":5501},{"id":5522,"depth":5410,"text":5523},{"id":7188,"depth":5378,"text":7189,"children":13706},[13707],{"id":7199,"depth":5410,"text":7200},{"id":7532,"depth":5378,"text":7533},{"id":7647,"depth":5378,"text":7648,"children":13710},[13711,13712,13713],{"id":7654,"depth":5410,"text":7655},{"id":7808,"depth":5410,"text":7809},{"id":7882,"depth":5410,"text":7883},{"id":7992,"depth":5378,"text":7993,"children":13715},[13716,13717],{"id":8007,"depth":5410,"text":8008},{"id":8033,"depth":5410,"text":8034},{"id":8746,"depth":5378,"text":8747,"children":13719},[13720],{"id":9743,"depth":5410,"text":9744},{"id":9883,"depth":5378,"text":9884},{"id":13105,"depth":5378,"text":13106,"children":13723},[13724],{"id":13201,"depth":5410,"text":13202},{"id":13323,"depth":5378,"text":13324},"Internal Covariate Shift, математика Batch Normalization, переваги та обмеження, train\u002Feval режими, практична реалізація у PyTorch та експериментальне порівняння з базовою архітектурою.","md",null,{},{"title":3964,"description":13726},"3gsDu8wzcP8HfU0iqgpPQ6AsKShZ9D7P9n4nAO3yL8c",[13733,13735],{"title":3960,"path":3961,"stem":3962,"description":13734,"children":-1},"Чому нульова ініціалізація не працює, математика Xavier та He ініціалізації, практичне застосування у PyTorch та експериментальне порівняння методів на глибоких мережах.",{"title":3968,"path":3969,"stem":3970,"description":13736,"children":-1},"Випадкове вимикання нейронів для боротьби з перенавчанням, математика та інтуїція Dropout, комбінування з BatchNorm і weight decay, експериментальне порівняння стратегій.",1791986836651]