A ready-to-run project that demonstrates MLflow experiment tracking — the practice of recording every important detail about a machine-learning training run (hyperparameters, evaluation scores, ...

This workflow demonstrates the end-to-end process of managing machine learning models with MLflow. It covers saving a trained model as a portable artifact, registering it in a central model registry ...