Description

MLflow is a machine learning lifecycle management solution designed for data science teams. It enables users to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry, record and query experiments including the code, data, config, and results, deploy machine learning models in diverse serving environments, store, annotate, discover, and handle models in a central repository, as well as log experiments using Python, REST, R API, and Java API APIs. Features include MLflow tracking, log parameters, code versions management, data visualizations, and built-in tracking server.