🚀 Day 7 of 30-Day MLOps Challenge content on Model Experiment Tracking with MLflow – “Log It or Lose It!”
📚 Key Learnings
Why experiment tracking is critical for MLOps: reproducibility, comparability, and collaboration
MLflow architecture: Tracking, Projects, Models, Registry
How to track experiments, runs, metrics, parameters, artifacts using MLflow...
