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  1. docs/en/docs/async.md

    * **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.
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  2. docs/pt/docs/async.md

    * **Machine Learning**: Normalmente exige muita multiplicação de matrizes e vetores. Pense numa grande planilha com números e em multiplicar todos eles juntos e ao mesmo tempo.
    
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  3. docs/es/docs/async.md

    * **Machine Learning**: normalmente requiere muchas multiplicaciones de "matrices" y "vectores". Piensa en una enorme hoja de cálculo con números y multiplicando todos juntos al mismo tiempo.
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  4. docs/en/data/external_links.yml

    link: https://eng.uber.com/ludwig-v0-2/ title: 'Uber: Ludwig v0.2 Adds New Features and Other Improvements to its Deep Learning Toolbox [including a FastAPI server]' - author: Maarten Grootendorst author_link: https://www.linkedin.com/in/mgrootendorst/ link: https://towardsdatascience.com/how-to-deploy-a-machine-learning-model-dc51200fe8cf title: How to Deploy a Machine Learning Model - author: Johannes Gontrum author_link: https://x.com/gntrm link: https://medium.com/@gntrm/jwt-authentication-w...
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  5. 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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  6. docs/de/docs/tutorial/path-params.md

    ///
    
    /// 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.
    
    ///
    
    ### Deklarieren Sie einen *Pfad-Parameter*
    
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  7. 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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  8. README.md

    ------------------- |
    [![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://www.tensorflow.org/api_docs/) |
    
    [TensorFlow](https://www.tensorflow.org/) is an end-to-end open source platform
    for machine learning. It has a comprehensive, flexible ecosystem of
    [tools](https://www.tensorflow.org/resources/tools),
    [libraries](https://www.tensorflow.org/resources/libraries-extensions), and
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  9. docs/fr/docs/tutorial/path-params.md

    ///
    
    /// tip | Astuce
    
    Pour ceux qui se demandent, "AlexNet", "ResNet", et "LeNet" sont juste des noms de <abbr title="Techniquement, des architectures de modèles">modèles</abbr> de Machine Learning.
    
    ///
    
    ### Déclarer un paramètre de chemin
    
    Créez ensuite un *paramètre de chemin* avec une annotation de type désignant l'énumération créée précédemment (`ModelName`) :
    
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  10. docs/ja/docs/tutorial/path-params.md

    ///
    
    /// tip | 豆知識
    
    "AlexNet"、"ResNet"そして"LeNet"は機械学習<abbr title="Technically, Deep Learning model architectures">モデル</abbr>の名前です。
    
    ///
    
    ### *パスパラメータ*の宣言
    
    次に、作成したenumクラスである`ModelName`を使用した型アノテーションをもつ*パスパラメータ*を作成します:
    
    {* ../../docs_src/path_params/tutorial005.py hl[16] *}
    
    ### ドキュメントの確認
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