MLflow

ML lifecycle platform. Experiment tracking, model registry, deployment, and reproducibility.

About MLflow

MLflow is an open source platform for managing the end-to-end machine learning lifecycle. It tackles experiment tracking, reproducibility, deployment, and a central model registry.

Key Features

Experiment tracking & comparison
Model registry with versioning
MLflow Projects for reproducibility
Model deployment (REST, Docker, cloud)
Plugin-based architecture
Integration with all major ML frameworks

Why choose MLflow?

MLflow is an open source alternative to Weights & Biases, Neptune. Licensed under Apache-2.0, it gives you full access to the source code and the freedom to modify, self-host, and contribute. You can deploy it on your own servers for complete data ownership and privacy.