MLflow
by Databricks · open-source · Last verified 2026-03-19
MLflow is an open-source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. It allows tracking experiments, packaging code into reproducible runs, and deploying models to various platforms.
https://mlflow.org/ ↗A
A—Great
Adoption: AQuality: AFreshness: ACitations: B+Engagement: A
Specifications
- License
- Apache 2.0
- Pricing
- open-source
- Capabilities
- experiment-tracking, model-packaging, model-deployment, model-registry
- Integrations
- Spark, Kubernetes, AWS SageMaker
- Use Cases
- ml-lifecycle-management, reproducible-research, continuous-integration, model-governance
- API Available
- Yes
- Tags
- mlops, machine-learning, experiment-tracking, model-registry, deployment
- Added
- 2026-03-19
- Completeness
- 100%
Index Score
82.4Adoption
85
Quality
82
Freshness
80
Citations
78
Engagement
83
Put AI to work for your business
Deploy this platform alongside autonomous AaaS agents that handle tasks end-to-end — no babysitting required.