Servindo modelos de ML em produção: FastAPI + Docker + AWS Lambda
📰 Medium · Python
Learn to serve ML models in production using FastAPI, Docker, and AWS Lambda for scalable and efficient deployment
Action Steps
- Build a RESTful API using FastAPI to serve ML models
- Containerize the API using Docker for easy deployment
- Configure AWS Lambda to handle API requests and scale automatically
- Test the deployment using sample data and verify model performance
- Deploy the model to a production environment and monitor its performance
Who Needs to Know This
Data scientists and machine learning engineers can benefit from this tutorial to deploy their models in a production-ready environment, while DevOps teams can use this to streamline their model serving pipeline
Key Insight
💡 Using FastAPI, Docker, and AWS Lambda allows for scalable and efficient deployment of ML models in production
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Serve ML models in production with FastAPI, Docker, and AWS Lambda!
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