Week 0 Overview

Welcome and Introduction

Wednesday, August 25 - Friday, August 27

• Lecture 8/26 (slides) (slides) (video)

Week 1 Overview

Maximum Likelihood and Multivariate Gaussians

Monday, August 30 - Friday, September 3

• Discussion 0 (solution)
• Homework 0
• Lecture 8/31 (slides) (video)
• Lecture 9/2 (slides) (video)

Week 2 Overview

Linear Regression and Classification

Tuesday, September 7 - Friday, September 10

• Discussion 1 (solution)
• Homework 1 (zip)
• Lecture 9/7 (slides) (video)
• Lecture 9/9 (slides) (slides) (video)

Week 4 Overview

Backpropagation, SGD, and Multiway Classification

Monday, September 20 - Friday, September 24

Week 5 Overview

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

Monday, September 27 - Friday, October 1

Week 6 Overview

PCA, Autoencoders, and Clustering

Monday, October 4 - Friday, October 8

Week 7 Overview

t-SNE and Kernel Methods

Monday, October 11 - Friday, October 15

• Midterm (Wed 10/13 7-9pm)

Week 8 Overview

Support Vector Machines

Monday, October 18 - Friday, October 22

Week 9 Overview

Convolutional Neural Networks and Applications in Vision

Monday, October 25 - Friday, October 29

Week 10 Overview

Nearest Neighbor and Metric Learning

Monday, November 1 - Friday, November 5

Week 11 Overview

Transformers

Monday, November 8 - Friday, November 12

Week 12 Overview

Language Models and Applications in Computational Biology

Monday, November 15 - Friday, November 19

Week 13 Overview

Graphical Models

Monday, November 22 - Wednesday, November 24

Week 14 Overview

Causality

Monday, November 29 - Friday, December 3