Outline

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Week 1 August 14, 2016
Chapter 1: Introduction

Week 2 August 21, 2016
Chapter 1: Introduction

Week 3 August 28, 2016
Project #1 due Sep. 1
Chapter 1: Introduction

Week 4 September 4, 2016
Chapter 1: Introduction
Chapter 2: Probability Distributions

Week 5 September 11, 2016
Project #2 due Sep. 15
Chapter 2: Probability Distributions

Week 6 September 18, 2016
Chapter 2: Probability Distributions
Chapter 9: (Gaussian) Mixture Models and EM

Week 7 September 25, 2016
Project #3 due Sep. 29
Chapter 3: Linear Models for Regression

Week 8 October 2, 2016
Chapter 4: Linear Models for Classification

Week 9 October 9, 2016
Project #4 due Oct. 13
Chapter 5: Neural Networks

Week 10 October 16, 2016
Oct. 20 Final project proposal due
Chapter 6: Kernel Methods

Week 11 October 23, 2016
Project #5 due Oct. 27
Chapter 7: Sparse Kernel Machines

Week 12 October 30, 2016
Chapter 7: Sparse Kernel Machines

Week 13 November 6, 2016
Project #6 due Nov. 10
Chapter 9: k-Means Algorithm

Week 14 November 13, 2016
Deep Learning

Week 15 November 20, 2016
Thanksgiving Break! (no classes)

Week 16 November 27, 2016
Final project due Dec. 2

Week 17 December 4, 2016
Final Project Presentations
Tuesday, Dec. 6, 3:30pm – 5:30pm
Wednesday, Dec. 7, 3:30pm – 5:30pm
Thursday, Dec. 8, 10:30am – 12:30pm