{* ../../docs_src/path_params/tutorial005_py310.py hl[1,6:9] *}

/// tip | Astuce

Si vous vous demandez, « AlexNet », « ResNet » et « LeNet » sont juste des noms de <dfn title="Techniquement, architectures de modèles de Deep Learning">modèles</dfn> de Machine Learning.

///

### Déclarer un paramètre de chemin { #declare-a-path-parameter }

* <dfn title="Un método de Machine Learning que usa redes neuronales artificiales con numerosas capas ocultas entre las capas de entrada y salida, desarrollando así una estructura interna completa">Deep Learning</dfn>

## Encabezados { #headings }

//// tab | Prueba

### Desarrolla una webapp - un tutorial { #develop-a-webapp-a-tutorial }

Hola.

{* ../../docs_src/path_params/tutorial005_py310.py hl[18,21,23] *}
На стороне клиента вы получите такой JSON-ответ:

```JSON
{
  "model_name": "alexnet",
  "message": "Deep Learning FTW!"
}
```

## Path-параметры, содержащие пути { #path-parameters-containing-paths }

Предположим, что есть *операция пути* с путем `/files/{file_path}`.

Sie können dem automatisch generierten Schema also zusätzliche Daten hinzufügen.

    }
}
```

### Özel OpenAPI *path operation* şeması { #custom-openapi-path-operation-schema }

`openapi_extra` içindeki dictionary, *path operation* için otomatik üretilen OpenAPI şemasıyla derinlemesine (deep) birleştirilir.

Böylece otomatik üretilen şemaya ek veri ekleyebilirsiniz.

* `bar` bir `str` olarak
* `baz` bir `list` olarak

* Tutorial - Kullanıcı kılavuzu
* İleri Düzey Kullanıcı Kılavuzu
* SQLModel dokümanları
* API dokümanları
* otomatik dokümanlar

* Veri Bilimi
* Deep Learning
* Machine Learning
* Dependency Injection
* HTTP Basic authentication
* HTTP Digest
* ISO formatı
* JSON Schema standardı
* JSON schema
* schema tanımı
* Password Flow
* Mobil

     * is the only one in use, but if we encounter nested concatenations, we start a deque of
     * meta-iterators rather than letting the nesting get arbitrarily deep.  This keeps each
     * operation O(1).
     */

    private @Nullable Iterator<? extends Iterator<? extends T>> topMetaIterator;

    // Only becomes nonnull if we encounter nested concatenations.

     * is the only one in use, but if we encounter nested concatenations, we start a deque of
     * meta-iterators rather than letting the nesting get arbitrarily deep.  This keeps each
     * operation O(1).
     */

    private @Nullable Iterator<? extends Iterator<? extends T>> topMetaIterator;

    // Only becomes nonnull if we encounter nested concatenations.

 * href="https://www.javadoc.io/doc/com.github.ben-manes.caffeine/caffeine/latest/com.github.benmanes.caffeine/com/github/benmanes/caffeine/cache/AsyncLoadingCache.html">their
 * deep support for asynchronous operations</a>. But if you want to migrate to Caffeine with minimal
 * code changes, you can use <a

* **Aprendizado de Máquina**: Normalmente exige muita multiplicação de matrizes e vetores. Pense numa grande planilha com números e em multiplicar todos eles juntos e ao mesmo tempo.