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 1 Overview

Welcome and Introduction

Week 2 Overview

Maximum Likelihood and Multivariate Gaussians

Week 3 Overview

Linear Regression and Classification

Week 4 Overview

Logistic Regression, Neural Networks, Backpropagation, and SGD

Week 5 Overview

Multiway Classification, Decision Theory, Bias-Variance, Over- and Under-Fitting

Week 6 Overview

ROC Curves, Precision/Recall, Dimensionality Reduction, and PCA

Week 7 Overview

t-SNE and Clustering

Week 8 Overview

Kernel Methods and Support Vector Machines

Week 9 Overview

Support Vector Machines, Nearest Neighbor, and Metric Learning

Week 10 Overview

Vision and Convolutional Neural Networks

Week 11 Overview

Decision Trees, Random Forests, and Transformers

Week 12 Overview


Week 13 Overview

Applications in Biology and Hidden Markov Models

Week 14 Overview

Probabilistic Graphical Models

Week 15 Overview

Causality and Reinforcement Learning

Lecture Slides and Videos