Black-Box and Glass-Box Explanation in Machine Learning
Offered By: Toronto Machine Learning Series (TMLS) via YouTube
Course Description
Overview
Explore the critical aspects of intelligibility and explanation in machine learning through this comprehensive conference talk by Rich Caruna, Sr. Principal Researcher at Microsoft Research. Delve into new methods for providing explanations and gain insights into the differences between Glass-Box and Black-Box ML explanation techniques. Learn how these approaches impact the understanding and interpretation of machine learning models, enhancing your ability to create more transparent and explainable AI systems.
Syllabus
Black-Box and Glass-Box Explanation in Machine Learning
Taught by
Toronto Machine Learning Series (TMLS)
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