Handouts
The lecture notes are available here.
| # | DATE | TOPIC | LINK |
|---|---|---|---|
| 1 | August 27 | Course Information | HTML |
| 2 | August 27 | Project Guidelines | HTML |
| 3 | September 3 | Project Topics, 1-page proposal due Sep 20 | |
| 4 | September 8 | Optional reading: Cover Trees for Nearest Neighbor | |
| 5 | September 9 | Homework 1, due Sep 22 | PDF. Data: NN, NN-NoMatlab, regression, regression-NoMatlab. |
| 6 | September 9 | Homework 1 Solution | |
| 7 | September 26 | Homework 2, due Oct 8 | PDF Data: astrophysics.zip, face-data.zip, face-code.zip, |
| 8 | Oct 16 | Homework 2 solution | PDF |
| 9 | Homework 3, due Nov 12 | PDF Data: inference skeleton code and data |
|
| 10 | Nov 19 | Homework 3 solution | PDF |
| 11 | Nov 23 | Homework 4, due Dec 3 | pdf Data: robot_no_momemtum.data, Data: robot_data2.data |
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.