(scroll down to check the course calendar)
| Week | Time | Activity | Assignment |
|
3.1 |
13:45 - 15:30, Feb 08, Tue. | Introduction | |
| 10:45 - 12:30, Feb 11, Fri. | Clustering; Nearest neighbor classification |
||
| 13:45 - 15:30, Feb 11, Fri. | Guided self study | ||
|
3.2 |
13:45 - 15:30, Feb 15, Tue. | Lab exercise | |
| 10:45 - 12:30, Feb 18, Fri. | Linear regression; Gradient descent |
Start A1 | |
| 13:45 - 15:30, Feb 18, Fri. | Lab: gradient descent | ||
|
3.3 |
13:45 - 15:30, Feb 22, Tue. | Group work on A1 | |
| 10:45 - 12:30, Feb 25, Fri. | Bayesian classification; Logistic regression |
||
| 13:45 - 15:30, Feb 25, Fri. | Group work on A1 | ||
|
3.4 |
13:45 - 15:30, Mar 01, Tue. | Group work on A1 | |
| 10:45 - 12:30, Mar 04, Fri. | Support vector machine | Due A1 Start A2 |
|
| 13:45 - 15:30, Mar 04, Fri. | Group work on A2 | ||
|
3.5 |
13:45 - 15:30, Mar 08, Tue. | Group work on A2 | |
| 10:45 - 12:30, Mar 11, Fri. | Decision trees; Random forest |
||
| 13:45 - 15:30, Mar 11, Fri. | Group work on A2 | ||
|
3.6 |
13:45 - 15:30, Mar 15, Tue. | Group work on A2 | |
| 10:45 - 12:30, Mar 18, Fri. | Neural networks | Due A2 | |
| 13:45 - 15:30, Mar 18, Fri. | Lab exercise | ||
|
3.7 |
13:45 - 15:30, Mar 22, Tue. | Lab exercise | |
| 10:45 - 12:30, Mar 25, Fri. | Deep learning | ||
| 13:45 - 15:30, Mar 25, Fri. | Lab exercise | ||
| 3.8 |
13:45 - 15:30, Mar 29, Tue. | Summary; Q&A |
|
| 3.9 |
No lecture. Self study (prepare for the final exam) | ||
| 3.10 | 09:00 - 11:30, Apr 12, Tue. | Final exam | |
| 4.9 | 09:00 - 11:30, Jun 14, Tue. | Resit | |
Copyright @Liangliang Nan. 2022