Do You Trust and Understand Your Predictive Models?

To help practitioners make the most of recent and disruptive breakthroughs in debugging, explainability, fairness, and interpretability techniques for machine learning, our friends over at H2O.ai have written and exciting eBook “An Introduction to Machine Learning Intrepretability Second Edition.” This report defines key terms, introduces the human and commercial motivations for the techniques, and discusses predictive modeling and machine learning from an applied perspective, focusing on the common challenges of business adoption, internal model documentation, governance, validation requirements, and external regulatory mandates.