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Explore the concept of VC dimension as a mechanism for describing the expressiveness of infinite hypothesis spaces in this lecture on computational learning theory. The 1 hour 19 minute session builds upon previous discussions in the field, providing deeper insights into how we can quantify the complexity of learning models. Visit the accompanying lecture notes for additional details and resources on computational learning theory.
Syllabus
Lecture 15: VC dimension
Taught by
UofU Data Science