MLflow
VerifiedOpen-source platform for managing the ML lifecycle including experimentation, reproducibility, deployment, and a central model registry. 18,000+ GitHub stars.
Frameworks Covered
NIST-AI-RMF
Services
experiment-trackingmodel-registrymodel-evaluationdeployment
About MLflow
MLflow is an open-source platform for managing the end-to-end machine learning lifecycle. It handles experiment tracking, model packaging, model registry, and deployment — with support for any ML library, algorithm, or deployment target.
Features
- Experiment tracking (parameters, metrics, artifacts)
- Model registry for versioning and stage management
- Model evaluation with automated metrics
- Model packaging for reproducible deployment
- MLflow Recipes for production-ready pipelines
- Supports LLM evaluation and tracking
- Integrates with popular ML libraries
Installation
pip install mlflow
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