Dynamic Models - Testing, Governance and Implementation
MLOps World: Machine Learning in Production via YouTube
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Learn how to implement dynamic models in production environments while maintaining proper governance and risk management controls in this conference talk from MLOps World. Explore the challenges of transitioning from static models that suffer from model, process, and data drift to dynamic models that can adapt over time. Discover a collaborative approach to developing model operation cycles that balance automation with necessary controls, enabling organizations to leverage the benefits of dynamic models without compromising their model risk posture. Gain insights into monitoring strategies, governance frameworks, and regulatory considerations specific to dynamic model implementations. Understand practical solutions for testing and validating dynamic models in real-world scenarios, drawing from experience in credit risk, fraud detection, and anti-money laundering applications within the banking industry.
Syllabus
Dynamic Models: Testing, Governance and Implementation
Taught by
MLOps World: Machine Learning in Production