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docs/en/docs/advanced/events.md
## Use Case Let's start with an example **use case** and then see how to solve it with this. Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖
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docs_src/path_params/tutorial005.py
app = FastAPI() @app.get("/models/{model_name}") async def get_model(model_name: ModelName): if model_name is ModelName.alexnet: return {"model_name": model_name, "message": "Deep Learning FTW!"} if model_name.value == "lenet": return {"model_name": model_name, "message": "LeCNN all the images"}
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docs/en/data/external_links.yml
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://twitter.com/gntrm
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docs/en/docs/advanced/index.md
Some course providers ✨ [**sponsor FastAPI**](../help-fastapi.md#sponsor-the-author){.internal-link target=_blank} ✨, this ensures the continued and healthy **development** of FastAPI and its **ecosystem**.
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docs/en/docs/async.md
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docs/es/docs/async.md
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docs/em/docs/tutorial/path-params.md
!!! info <a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">🔢 (⚖️ 🔢) 💪 🐍</a> ↩️ ⏬ 3️⃣.4️⃣. !!! tip 🚥 👆 💭, "📊", "🎓", & "🍏" 📛 🎰 🏫 <abbr title="Technically, Deep Learning model architectures">🏷</abbr>. ### 📣 *➡ 🔢* ⤴️ ✍ *➡ 🔢* ⏮️ 🆎 ✍ ⚙️ 🔢 🎓 👆 ✍ (`ModelName`): ```Python hl_lines="16" {!../../../docs_src/path_params/tutorial005.py!} ``` ### ✅ 🩺
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docs/tr/docs/project-generation.md
... müsaitliğime ve diğer faktörlere bağlı olarak daha sonra gelebilir. 😅 🎉 ## Machine Learning modelleri, spaCy ve FastAPI GitHub: <a href="https://github.com/microsoft/cookiecutter-spacy-fastapi" class="external-link" target="_blank">https://github.com/microsoft/cookiecutter-spacy-fastapi</a> ### Machine Learning modelleri, spaCy ve FastAPI - Features * **spaCy** NER model entegrasyonu.
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docs/es/docs/tutorial/path-params.md
!!! tip "Consejo" Si lo estás dudando, "AlexNet", "ResNet", y "LeNet" son solo nombres de <abbr title="Técnicamente, arquitecturas de modelos de Deep Learning">modelos</abbr> de Machine Learning. ### Declara un *parámetro de path* Luego, crea un *parámetro de path* con anotaciones de tipos usando la clase enum que creaste (`ModelName`): ```Python hl_lines="16"
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docs/pt/docs/async.md
* **Machine Learning**: Normalmente exige muita multiplicação de matrizes e vetores. Pense numa grande folha de papel com números e multiplicando todos eles juntos e ao mesmo tempo.
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