MIT: Machine Learning 6.036, Lecture 5: Regression (Fall 2020)

Lecture 5 for the MIT course 6.036: Introduction to Machine Learning (Fall 2020 Semester) Full lecture information and slides: http://tamarabroderick.com/ml.html Lecture date: 2020 / 09 / 29 Lecturer: Tamara Broderick Lecture TAs: Crystal Wang and Satvat Jagwani If you find any ways to improve how well the video captions reflect the live lectures, please submit a pull request to: https://github.com/tbroderick/ml_6036... 0:00:00 Overview & Review of classification 0:05:03 Compare to regression 0:12:23 Linear regression 0:23:34 Linear regression: A Direct Solution 0:43:58 What can go wrong in practice? 0:53:48 Regularizing linear regression 1:07:47 Some notes on features 1:13:27 Optimizing linear regression 1:17:50 Gradient descent for linear regression 1:19:44 Stochastic gradient descent