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Lecture
PAC Learning: Empirical Risk Minimization
Description
This lecture delves into quantifying how much an algorithm learns using the PAC learning framework, introducing the Empirical Risk Minimization principle, discussing the ill-posed nature of learning, the need for inductive bias, and different predictor/hypothesis spaces.
Official source
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