Handouts
The lecture notes are available here.
| # | DATE | TOPIC | LINK |
|---|---|---|---|
| 1 | Aug 26 | Course Information | HTML |
| 2 | Aug 26 | Project Guidelines | HTML |
| 3 | Aug 31 | Linear Algebra review | |
| 4 | September 2 | Homework 1, due Sep 21 | PDF. Data: NN, NN-NoMatlab, regression, regression-NoMatlab. |
| 5 | September 8 | Optional reading: Cover Trees for Nearest Neighbor | |
| 7 | Sep 28 | Homework 2, due Oct 8 | PDF Data: astrophysics.zip, face-data.zip, face-code.zip, NN, NN-NoMatlab. (If it applies, you can do the programming part of SVm question on your project's dataset.) |
| 9 | Oct 18 | Homework 3, due Nov 11 | PDF |
| 10 | Oct 27 | Midterm Survey | |
| 11 | Homework 4, due Dec 3 | pdf Data: discretemrf-cs6780.txt |
|
| 12 | Reviewing instructions, due Dec 10 | Review Instructions |
Other resources
- Matrix
- Matrix Cookbook
- Matlab
- Here are a couple of Matlab tutorials that you might find helpful:
Matlab tutorial 1
Matlab tutorial 2
Examples of machine learning algorithms. - Data
- Here is the UCI Machine learning repository, which contains a large collection of standard datasets for testing learning algorithms. If you want to see examples of recent work in machine learning, start by taking a look at the conferences NIPS (all old NIPS papers are online) and ICML. Some other related conferences include UAI, AAAI, IJCAI.