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MLflow is an open-source platform designed to manage the machine learning lifecycle, including experimentation, reproducibility, and deployment. It provides a comprehensive set of tools for tracking experiments, packaging code into reproducible runs, and sharing and deploying models across various environments.

It can be seamlessly integrated with nearly no code changes into models using the Lightning framework, but it also supports other frameworks like TensorFlow, Scikit-learn, and XGBoost.