MLflow is an open-source platform for managing the complete machine learning lifecycle, including experimentation, reproducibility, and deployment. It provides tools to track experiments, package models, and deploy them in production environments.

Features of MLflow:

Experiment tracking to log and compare results of machine learning models.
Model registry for versioning, managing, and deploying ML models.
Support for multiple machine learning libraries and frameworks.
Scalable and flexible integration with cloud and on-premises environments.
Comprehensive APIs and UI for streamlined workflow management.

To Check the version of MLflow : mlflow --version

Disclaimer: MLflow is an open-source software distributed under the Apache License 2.0. It is not affiliated with, endorsed by, or sponsored by any other company. MLflow is provided "as is," without any warranty, express or implied. Users utilize this software at their own risk. The developers and contributors to MLflow hold no responsibility for any damages, losses, or consequences resulting from the use of this software. Users are advised to carefully review and comply with licensing terms and any applicable regulations while using MLflow.

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