Understand SHAP (SHapley Additive exPlanations)
Hosted by Patrick Hall
Go deeper with a course
What you'll learn
SHAP - The Good, Bad & Ugly
The Good
How SHAP helps explain tree-based models accurately.
The Bad
Common issues like correlation, variance, and calculation time.
The Ugly
Complexities of using SHAP effectively.
Why this topic matters
Explore explainable artificial intelligence (XAI) and learn how to interpret and explain sophisticated ML/AI algorithms.
You'll learn from
Patrick Hall
Principal Scientist, HallResearch.ai & Assistant Professor, GWSB
Patrick Hall is the principal scientist at HallResearch.ai. He is also an assistant professor of decision sciences at the George Washington University School of Business, teaching data ethics, business analytics, and machine learning classes. Patrick conducts research in support of NIST's AI Risk Management Framework, works with leading fair lending and AI risk management advisory firms, and serves on the board of directors for the AI Incident Database.