| Class # | Date | Lecture Topic | Reading | Slides | Assignments | |||||
| Week 1 | ||||||||||
| 1 | 8/27 | Course Overview; Introduction to Machine Learning | I2ML: Ch. 1 | slides1 | ||||||
| 2 | 8/29 | Supervised Learning | I2ML: Sec. 2.1-2.4 | slides2 | ||||||
| Week 2 | ||||||||||
| 3 | 9/3 | Supervised Learning (cont) | I2ML: 2.5-2.8 | slides3 | ||||||
| 4 | 9/5 | Bayesian Decision Theory | I2ML: Ch 3 | slides4 | ||||||
| Week 3 | ||||||||||
| 5 | 9/10 | Parametric Methods | I2ML: Ch 4 | slides5 | HW1.pdf | |||||
| 6 | 9/12 | Parametric Methods | I2ML: Ch 4 | slides6 | ||||||
| Week 4 | ||||||||||
| 7 | 9/17 | Parametric Methods (cont) | I2ML: Ch 4 | slides7 | ||||||
| 8 | 9/19 | Multivariate Method | I2ML: Ch 5 | slides8 pdf | Homework 1 Due | |||||
| Week 5 | ||||||||||
| 9 | 9/24 | Dimensionality Reduction | I2ML: Ch 6 | slides9 pdf | ||||||
| 10 | 9/26 | Dimensionality Reduction | I2ML: Ch 6 | slides 10 pdf | ||||||
| Week 6 | ||||||||||
| 11 | 10/1 | Clustering | I2ML: Ch 7 | slides 11 pdf | Project Proposal Due | |||||
| 12 | 10/3 |
Decision Trees
| I2ML: Ch 9 | slides 12 pdf | hw2.pdf decisiontree.xls | |||||
| Week 7 | ||||||||||
| 13 | 10/8 | Decision Trees | I2ML: Ch 9 | slides 13 pdf | ||||||
| 14 | 10/10 | Linear Discrimination | I2ML: Ch 10 | slides 14 pdf | ||||||
| Week 8 | ||||||||||
| 15 | 10/15 | Linear Discrimination | I2ML: Ch 9 | slides 15 | ||||||
| 16 | 10/17 | Midterm Exam | ||||||||
| Week 9 | ||||||||||
| 17 | 10/22 | Kernel Machines | I2ML: Ch 13 | slides 16 | ||||||
| 18 | 10/24 | Kernel Machines | I2ML: Ch 13 | slides 17 | ||||||
| Week 10 | ||||||||||
| 19 | 10/29 | Hidden Markov Models | I2ML: Ch 15 | slides 18 | ||||||
| 20 | 10/31 | Hidden Markov Models (cont) | I2ML: Ch 15 | slides 19 | ||||||
| Week 11 | ||||||||||
| 21 | 11/5 | Hidden Markov Models (cont) |
I2ML: Ch 15 | slides 20 | ||||||
| 22 | 11/7 | Reinforcement Learning | I2ML: Ch 18 | slides 21 | Project Progress Report | |||||
| Week 12 | ||||||||||
| 23 | 11/12 | Reinforcement Learning | I2ML: Ch 18 | slides 22 | hw3.pdf | |||||
| 24 | 11/14 | Reinforcement Learning | I2ML: Ch 15 | Extra notes Examples | ||||||
| Week 13 | ||||||||||
| 25 | 11/19 | Bayesian Networks | I2ML: Ch 15 | |||||||
| 26 | 11/21 | Bayesian Networks(cont) | I2ML: Ch 15 | slides 24 | Extra slides | |||||
| Week 14 | ||||||||||
| 27 | 11/26 | Multilayer Perceptrons | I2ML: Ch 15 | slides 25 | Intro to Deep Learning | |||||
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| Week 15 | ||||||||||
| 28 | 12/3 | Multilayer Perceptrons | I2ML: Ch 15 | hw4.pdf | 26 | 12/5 | Final Exam Review/Quesions |
| slides 26 |
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