MLflow
Open-source ML lifecycle management for tracking, packaging, and deploying models.
About MLflow
Open-source platform for the complete ML lifecycle. Track experiments, package models, manage model registry, and serve predictions. Framework-agnostic and integrates with all major ML libraries and cloud platforms.
Key Features
- Experiment tracking
- Model packaging
- Model registry
- Model serving
- Open source
- Framework agnostic
Pricing
free
Completely free and open source. Managed versions available through Databricks and cloud providers.
Pros
- Completely free
- Framework agnostic
- Strong community
- Cloud integrations
Cons
- Requires self-hosting
- UI is basic
- Less opinionated than alternatives