CS 189 at UC Berkeley
Introduction to Machine Learning
Lectures: 9:30 - 11 am Tu-Th in Li Ka Shing 245
Week 0 Overview
Linear Regression, Features, Hyperparameters and Cross-Validation
See Syllabus for more information. You can find a list of week-by-week topics. Notes are not a substitute for going to lecture, as additional material may be covered in lecture. Notes are from a previous iteration of the course and may not be comprehensive. Refer to lectures.
The discussion sections may cover new material and will give you additional practice solving problems. You can attend any discussion section you like. See Syllabus for more information.
All homeworks are fully graded. Your lowest homework score will be dropped, but this drop should be reserved for emergencies. See Syllabus for more information.