Free courses from frontend to fullstack and AI
AI, Data Science & Business Certificates from Google, IBM & Microsoft
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
Explore regularized least squares in this comprehensive lecture by Lorenzo Rosasco from MIT, University of Genoa, and IIT. Delve into key concepts including loss functions, optimality conditions, quadratic programming, and gradient descent. Learn about the class of numbers, super vectors, and perception as part of the 9.520/6.860S Statistical Learning Theory and Applications course. Gain valuable insights into statistical learning theory and its practical applications over the course of 80 minutes.
Syllabus
Introduction
Loss function
Optimality Condition
Quadratic Programming
Class of Numbers
SuperVectors
Perception
Gradient Descent
Taught by
MITCBMM