CS 189 at UC Berkeley

Introduction to Machine Learning

Lectures: T/Th 3:30-5 p.m., 155 Dwinelle

Professor Jennifer Listgarten

jennl [at] berkeley.edu

Office Hours: Tu/Th 5-6 p.m. (see calendar)

Professor Anant Sahai

sahai (at) eecs.berkeley.edu

Office Hours: Tu/Th 5-6 p.m. (see calendar)

Week 0 Overview

Least Squares Framework

Week 1 Overview

Features, Regularization, Hyperparameters and Cross-Validation

Week 2 Overview

MLE, MAP, OLS, Bias-Variance Tradeoffs

Week 3 Overview

Weighted LS, Total LS, Eigenmethods

Week 5 Overview

CCA, Nonlinear LS, Gradient Descent

Week 6 Overview

Neural Nets, Stochastic Gradient Descent

Week 7 Overview

Regression for Classification: Generative v. Discriminative

Week 10 Overview

Spring Break

Week 11 Overview

Decision Trees, Boosting, Ensemble Methods

Week 12 Overview

Convolutional Neural Nets, Regularization Revisited

Week 13 Overview

Unsupervised Learning: Nearest Neighbors

Week 14 Overview

Sparsity and Decision Trees