Model lineage tracks the complete lifecycle of a machine learning model, from training data and code to deployment. It provides a detailed audit trail, enabling teams to reproduce results, debug issues, and ensure regulatory compliance. Data scientists, ML engineers, and auditors benefit by gaining full transparency, improving model governance, and accelerating troubleshooting. This practice is essential for building trustworthy and maintainable AI systems.
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