CS 189/289A at UC Berkeley

Introduction to Machine Learning

Lectures: Tues & Thurs 2-3:30 pm online (Berkeley Academic Guide page)

Jennifer Listgarten

Make private Piazza post before emailing.

Office Hours: TBD

Jitendra Malik

Make private Piazza post before emailing.

Office Hours: TBD

Week 0 Overview

Welcome and Introduction

Week 1 Overview

Maximum Likelihood and Multivariate Gaussians

Week 2 Overview

Linear Regression and Classification

Week 3 Overview

Logistic Regression and Neural Networks

Week 4 Overview

Backpropagation, SGD, and Multiway Classification

Week 5 Overview

ROC Curves, Precision/Recall, Decision Theory, Bias-Variance, Over- and Under-Fitting

Week 6 Overview

PCA, Autoencoders, and Clustering

Week 7 Overview

t-SNE and Kernel Methods

  • Midterm (Wed 10/13 7-9pm)

Week 8 Overview

Support Vector Machines

Week 9 Overview

Convolutional Neural Networks and Applications in Vision

Week 10 Overview

Nearest Neighbor and Metric Learning

Week 11 Overview


Week 12 Overview

Language Models and Applications in Computational Biology

Week 13 Overview

Graphical Models

Week 14 Overview


Lecture Slides and Videos