Model Match

Model Match: Open-Source Machine Learning Model Management Platform

Model Match is an open-source machine learning model management platform that helps data scientists organize, track, version, and monitor their models in production. It provides a central registry for models and enables governance through lifecycle management, reproducibility, and operational visibility.

What is Model Match?

Model Match is an open-source machine learning model management platform that helps data scientists organize, track, version, and monitor their models in production. It provides the following key capabilities:

• Central model registry - Serves as a single source of truth for models, their versions, and metadata like training data used, performance metrics, owners etc.
• Model lineage and reproducibility - Logs model lineage from raw data to production model, enabling reproducibility of models.
• Model lifecycle management - Supports the entire model lifecycle from development to production deployment with stage-gated workflows.
• Integration with ML platforms - Integrates with popular ML platforms like TensorFlow, PyTorch, sklearn etc. to import models.
• Model monitoring - Monitors model performance metrics and data drift to detect issues with production models.
• Model governance - Provides oversight into models via dashboards, reports and automation of processes like model review/approval.

By providing these capabilities for production machine learning workflows, Model Match enables organizations to increase productivity of data scientists, reduce risks and improve governance over ML models.

Model Match Features

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