Mitchell Chapter Naive Bays vs Logistic Regression
| Date | Reading | Assignment | |
|---|---|---|---|
| 1/23 (Thurs.) | Chapter 1 | Course Overview, Intro to AI | |
| Search and Planning | |||
| 1/28 (Tues.) | Chapter 3 (Sec 1-4) | Problem Solving and Search | Project 1 (Search) out |
| 1/30 (Thurs.) | Chapter 3 (Sec 5-7) | Informed Search Algorithms | |
| 2/4 (Tues.) | Chapter 4 (Sec 1-2) | Local Search Algorithms | |
| 2/6 (Thurs.) | Chapter 5 (Sec 1-3) | Adversarial Search Algorithms | Project 1 due |
| Uncertainty | |||
| 2/11 (Tues.) | Jaynes (Chapter 1) | Plausible Reasoning | Project 2 (Localization) out |
| 2/13 (Thurs.) | Jaynes (Chapter 2> | The Quantitative Rules | |
| President's Day | |||
| 2/20 (Thurs.) | Chapter 14 (Sec 1-3) | Baysian Networks | |
| 2/25 (Tues.) | Chapter 14 (Sec 4-5) | Inference in Baysian Networks | |
| 2/27 (Thurs.) | Application: SLAM | Project 2 due | |
| 3/4 (Tues.) | Review | ||
| 3/6 (Thurs.) | Midterm (in class) | ||
| Decision Making | |||
| 3/11 (Tues.) | Chapter 15 | Making Simple Decisions | Project 3 (Bayesian Spam Filtering) out |
| 3/13 (Thurs.) | Chapter 18 (Sec 1-3) | Learning from Observations | |
| 3/18 (Tues.) | Mitchell Chapter | Naive Bayes and Logistic Regression | |
| 3/20 (Thurs.) | Application: Object Recognition | ||
| Spring Break | |||
| 4/1 (Thurs.) | Chapter 17 (Sec 1-2) | Sequential Decision Problems and MDPs | Project 4 ( |
| 4/3 (Tues.) | Chapter 21 (Sec 1-3) | Reinforcement Learning | |
| 4/7 (Thurs.) | Chapter 21 (Sec 5) | Policy Search | |
| 4/10 (Tues.) | |||
| 4/15 (Thurs.) | |||
| 4/17 (Tues.) | |||
| 4/22 (Thurs.) | |||
| Reading Period | |||
| 5/6 (Tues.) | Final Review |
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