Explore the fundamental concepts of generalization in machine learning through this comprehensive lecture from the Deep Learning Boot Camp. Join renowned experts Peter Bartlett from UC Berkeley and Sasha Rakhlin from MIT as they delve into the intricacies of generalization theory, perceptron algorithms, and their implications for deep learning. Gain valuable insights into how machine learning models can effectively learn from data and apply that knowledge to new, unseen examples. Engage with thought-provoking remarks and participate in a stimulating Q&A session to deepen your understanding of these crucial topics in the field of artificial intelligence and machine learning.
Overview
Syllabus
Introduction
Generalization
Perceptron
Remarks
Questions
Taught by
Simons Institute
