MLflow Overview

MLflow is an open-source platform that helps manage the entire machine learning lifecycle, including experimentation, reproducibility, deployment, and model management. It provides four core components:

1. MLflow Tracking:

   Tracks experiments to log and query results such as parameters, metrics, and models.

2. MLflow Projects:

   Defines and packages code in a reusable and reproducible format for running machine learning workflows.

3. MLflow Models:

   Manages and stores machine learning models in various formats for deployment across different platforms.

4. MLflow Registry:

   A central repository for managing the lifecycle of machine learning models, including versioning and stage transitions.

For more information, visit the MLflow website.

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