Model governance ensures responsible AI and machine learning lifecycle management. It establishes policies for model development, validation, deployment, and monitoring. This framework tracks performance, detects drift, and enforces compliance with regulations. Data scientists, risk officers, and business leaders benefit through reduced bias, improved transparency, and trustworthy, auditable decision-making systems.
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