MLflow
An open-source platform for managing the complete machine learning lifecycle, including experiment tracking, model packaging, deployment, and registry.
Components
Tracking: Log parameters, metrics, and artifacts. Projects: Package ML code for reproducibility. Models: Standard format for model packaging. Registry: Centralized model store with versioning and staging.
Usage
MLflow is the most widely used open-source MLOps tool. It integrates with all major ML frameworks and can run locally or on managed platforms like Databricks.