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Update README.md
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Signed-off-by: Ramin Mohammadi <26876927+raminmohammadi@users.noreply.github.com>
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raminmohammadi authored Sep 14, 2024
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In this Lab, we will learn how to expose ML models as APIs using [FastAPI](https://fastapi.tiangolo.com/) and [uvicorn](https://www.uvicorn.org/).
1. **FastAPI**: FastAPI is a modern, fast (high-performance), web framework for building APIs with Python based on standard Python type hints.
2. **uvicorn**: Uvicorn is an [ASGI](https://youtu.be/vKjCkeJGbNk) web server implementation for Python. It is often used to serve FastAPI aplications.
2. **uvicorn**: Uvicorn is an [Asynchronous Server Gateway Interface - ASGI](https://youtu.be/vKjCkeJGbNk) web server implementation for Python. It is often used to serve FastAPI aplications.

The workflow involves the following steps:
1. Training a Decision Tree Classifier on Iris Dataset.
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"detail": "Item with ID 1 not found"
}
```
- For more information on how to handle errors in FASTAPI refer to this [documentation](https://fastapi.tiangolo.com/tutorial/handling-errors/).
- For more information on how to handle errors in FASTAPI refer to this [documentation](https://fastapi.tiangolo.com/tutorial/handling-errors/).

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