Mlflow

If you're doing any serious machine learning work, you're probably already familiar with MLflow or should be. This skill brings experiment tracking, model registry, and deployment workflows into your Claude Code environment. It's framework-agnostic, so whether you're using PyTorch, TensorFlow, or scikit-learn, it handles the lifecycle stuff: logging parameters and metrics, versioning models, comparing runs, and pushing to production. With 20,000+ organizations using it and 23k GitHub stars, it's become the de facto standard for ML operations. The skill failed a Snyk security audit though, so check what that's about before using it in production environments.