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, Neural Networks, Backpropagation, and SGD

Week 4 Overview

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

Week 5 Overview

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

Week 6 Overview

t-SNE and Clustering

Week 7 Overview

Kernel Methods and Support Vector Machines

Week 8 Overview

Support Vector Machines and Convolutional Neural Networks

Week 9 Overview

Applications in Vision and Nearest Neighbor

Week 10 Overview

Metric Learning and Transformers

Week 11 Overview

Language Models

Week 12 Overview

Applications in Computational Biology and Graphical Models

Week 13 Overview

Graphical Models

Week 14 Overview


Lecture Slides and Videos