Learn ML deployment using FastAPI, Docker, CI/CD, and Cloud platforms
What you will learn
Deploy machine learning models in production using FastAPI and Docker.
Create APIs for ML models using FastAPI with optimized endpoints.
Containerize ML applications with Docker for scalable deployments.
Set up CI/CD pipelines for automated deployment and testing.
Train, evaluate, and save ML models, focusing on real-world datasets.
Deploy ML models to cloud platforms like Heroku and Microsoft Azure.
Build and integrate a simple frontend for ML model APIs.
Implement logging, error handling, and request handling in APIs.
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