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Understand SHAP (SHapley Additive exPlanations)

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Patrick Hall

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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.

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