Learn about the concluding concepts of VC dimensions and computational learning theory in this advanced machine learning lecture, exploring theoretical frameworks that help understand the complexity and learnability of hypothesis classes. Delve into mathematical foundations that bridge the gap between theoretical machine learning concepts and their practical applications, building upon previous discussions of VC theory.
Machine Learning: Understanding VC Dimensions and Computational Learning Theory - Lecture 18
Overview
Syllabus
Machine Learning: Lecture 18a: VC dimensions (continued)
Taught by
UofU Data Science
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