CS 189 at UC Berkeley

Introduction to Machine Learning

Lectures: M-Th 6:30-8:00 PM in VLSB 2060

Instructor Marc Khoury

khoury [at] eecs.berkeley.edu

Instructor Brijen Thananjeyan

bthananjeyan [at] berkeley.edu

Office Hours: Wed 11AM-12PM (Soda 341B)

Week 1 Overview

Introduction, Linear Classifiers, Perceptron Learning, and the support vector classifier

Week 2 Overview

Machine learning abstractions, Decision theory, and Gaussian discriminant analysis

Week 3 Overview

Eigenvectors, Quadratic Forms, Normal distributions, Regression, Newton's method and logistic regression

Week 4 Overview

Statistical justifications for regression, Ridge regression


There is no textbook for this class, and we do not plan on posting lecture slides. Instead, see Shewchuk's lecture notes and "A Comprehensive Guide to Machine Learning" on our Resources page, which cover a large portion of the material covered in lecture. We will follow Shewchuk's lecture notes closely. Notes are not a substitute for going to lecture, as additional material may be covered in lecture.


All homeworks are fully graded. See Syllabus for more information.