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docs/de/docs/_llm-test.md
* <abbr title="Eine Methode des Machine Learning, die künstliche neuronale Netze mit zahlreichen versteckten Schichten zwischen Eingabe- und Ausgabeschicht verwendet und so eine umfassende interne Struktur entwickelt">Deep Learning</abbr> ### Das abbr gibt eine vollständige Phrase und eine Erklärung { #the-abbr-gives-a-full-phrase-and-an-explanation }
Registered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Wed Dec 17 07:17:04 UTC 2025 - 12.6K bytes - Viewed (0) -
docs/es/docs/async.md
Eso, más el simple hecho de que Python es el lenguaje principal para **Data Science**, Machine Learning y especialmente Deep Learning, hacen de FastAPI una muy buena opción para APIs web de Data Science / Machine Learning y aplicaciones (entre muchas otras).
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docs/es/docs/tutorial/path-params.md
/// tip | Consejo Si te estás preguntando, "AlexNet", "ResNet" y "LeNet" son solo nombres de <abbr title="Técnicamente, arquitecturas de modelos de Deep Learning">modelos</abbr> de Machine Learning. /// ### Declarar un *path parameter* { #declare-a-path-parameter } Luego crea un *path parameter* con una anotación de tipo usando la clase enum que creaste (`ModelName`):
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docs/en/docs/_llm-test.md
* <abbr title="A group of machines that are configured to be connected and work together in some way.">cluster</abbr> * <abbr title="A method of machine learning that uses artificial neural networks with numerous hidden layers between input and output layers, thereby developing a comprehensive internal structure">Deep Learning</abbr> ### The abbr gives a full phrase and an explanation { #the-abbr-gives-a-full-phrase-and-an-explanation }
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docs/uk/docs/tutorial/path-params.md
/// /// tip | Порада Якщо вам цікаво, "AlexNet", "ResNet" та "LeNet" — це просто назви ML моделей <abbr title="Технічно, архітектури Deep Learning моделей">Machine Learning</abbr>. /// ### Оголосіть *параметр шляху* Потім створіть *параметр шляху* з анотацією типу, використовуючи створений вами клас enum (`ModelName`):
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docs/en/docs/async.md
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docs/de/docs/tutorial/path-params.md
{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *} /// tip | Tipp Falls Sie sich fragen, was „AlexNet“, „ResNet“ und „LeNet“ ist, das sind Namen von <abbr title="Genau genommen, Deep-Learning-Modellarchitekturen">Modellen</abbr> für maschinelles Lernen. /// ### Einen *Pfad-Parameter* deklarieren { #declare-a-path-parameter }Registered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Wed Dec 17 20:41:43 UTC 2025 - 10.5K bytes - Viewed (0) -
docs/fr/docs/async.md
* L'apprentissage automatique (ou **Machine Learning**) : cela nécessite de nombreuses multiplications de matrices et vecteurs. Imaginez une énorme feuille de calcul remplie de nombres que vous multiplierez entre eux tous au même moment.
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docs/es/docs/_llm-test.md
* <abbr 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</abbr> ### El abbr da una frase completa y una explicación { #the-abbr-gives-a-full-phrase-and-an-explanation }
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docs/pt/docs/_llm-test.md
Algum texto /// /// check | Verifique Algum texto /// /// tip | Dica Algum texto /// /// warning | Atenção Algum texto /// /// danger | Cuidado Algum texto /// //// //// tab | Informações Abas e blocos `Info`/`Note`/`Warning`/etc. devem ter a tradução do seu título adicionada após uma barra vertical (`|`).
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