Overview
End-to-end ML project: data ETL, model training, API serving, and containerized deployment.
Features
- Preprocessing pipeline
- Deployed REST API
- Basic UI
Challenges
- Feature drift handling
- Model versioning
End-to-end ML project: data ETL, model training, API serving, and containerized deployment.