CS189

CS 189 at UC Berkeley

Introduction to Machine Learning

Lectures: T/Th 12:30-2 p.m., 155 Dwinelle

Instructor Stella Yu

stellayu (at) berkeley.edu

Office Hours: Tu/Th 2-3 p.m. 400 Cory (see calendar)

Professor Anant Sahai

sahai (at) eecs.berkeley.edu

Office Hours: Tu/Th 2-3 p.m. 400 Cory (see calendar)

Week 1 Overview

Least Squares Framework

Week 2 Overview

Features, Regularization, Hyperparameters and Cross-Validation

Week 3 Overview

MLE, MAP, OLS, Bias-Variance Tradeoffs

Week 4 Overview

Weighted LS, Total LS, Eigenmethods

Week 5 Overview

CCA, Feature Discovery, Nonlinear LS, Gradient Descent

Discussions

The discussion sections may cover new material and will give you additional practice solving problems. You can attend any discussion section you like. However, if there are fewer desks than students, then students who are officially enrolled in the course will get seating priority. See Syllabus for more information.

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Homeworks

All homeworks are graded and it is highly-recommended that you do them. Your lowest homework score will be dropped, but this drop should be reserved for emergencies. See Syllabus for more information.

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