Basic Learning Theory - Lecture 3

Explore fundamental concepts in machine learning theory through this lecture delivered by Karthik Sridharan at the International Centre for Theoretical Sciences. Delve into the mathematical foundations that underpin modern data science and machine learning algorithms as part of the comprehensive "Data Science: Probabilistic and Optimization Methods II" program. Learn about core theoretical principles that enable current successes and future breakthroughs in machine learning, with particular emphasis on how rigorous theory informs the development of robust and adaptable systems. Gain insights into the probabilistic and optimization methods that form the backbone of contemporary data science applications. This educational content is part of a larger workshop featuring leading researchers and practitioners, organized with support from Google, Microsoft Research India, and the Safexpress Centre for Data, Learning and Decision Sciences at Ashoka University, designed to bridge theoretical foundations with practical applications in machine learning and data science.