Data and Model Versioning Strategy
Managing versions in an ML project
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My ML project involves regular data and model updates. Propose a complete versioning strategy using DVC or MLflow: how to version datasets, features, trained models, how to trace data lineage, and how to roll back if a new model degrades performance.
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