In this article, you will learn how to package a trained machine learning model behind a clean, well-validated HTTP API using FastAPI, from training to local testing and basic production hardening.
Topics we will cover include:
- Training, saving, and loading a scikit-learn pipeline for inference
- Building a FastAPI app with strict input validation via Pydantic
- Exposing, testing, and hardening a prediction endpoint with health checks
Let’s explore these techniques.
I definitely enjoy how simple it is to use FastAPI.