About MLflow
An open-source platform for the ML lifecycle that provides experiment tracking, a model registry, and deployment tools to productionize models.
Key Features
- Experiment tracking — record runs, parameters, metrics, and artifacts with a UI.
- Model Registry — a central store for model versions, stages, and metadata.
- Deployment tooling — APIs and tools to deploy models to various targets (Docker, Kubernetes, cloud services).
- Open-source & extensible — community maintained project with SDKs and integrations.
Use Cases & Best For
Organizations seeking an open-source, extensible ML lifecycle platform.
Teams that want integrated tracking, model registry, and deployment workflows.
About MLOps & Monitoring
Model operations and lifecycle management