MLflow

MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components: 1.) MLflow Tracking - Record and query experiments: code, data, config, and results 2.) MLflow Projects - Package data science code in a format to reproduce runs on any platform 3.) MLflow Models - Deploy machine learning models in diverse serving environments 4.) Model Registry - Store, annotate, discover, and manage models in a central repository View code on GitHub here: https://github.com/mlflow/mlflow/ To discuss or get help, please join our mailing list [email protected]