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      <title>Self-Hosted Model Registry &amp; Model Versioning: MLflow vs ClearML vs DVC</title>
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      <description>&lt;p&gt;As machine learning models move from experimental notebooks to production systems, managing model versions, tracking lineage, and controlling deployment stages becomes critical. A model registry provides a centralized store for model artifacts, metadata, and lifecycle management — from initial training through staging to production deployment.&lt;/p&gt;</description>
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