(scroll down to check the course calendar)
| Week | Topic/Activity | Assignment |
|
3.1 |
Introduction | |
| Linear regression; Gradient descent | Start A1 | |
| Lab exercise/Group work on A1 | ||
|
3.2 |
Lab exercise/Group work on A1 | |
| Clustering; Nearest neighbor classification | ||
| Lab exercise/Group work on A1 | ||
|
3.3 |
Lab exercise/Group work on A1 | |
| Bayesian classification; Logistic regression | ||
| Lab exercise/Group work on A1 | ||
|
3.4 |
Lab exercise/Group work on A1 | |
| Support vector machine | Due A1; Start A2 | |
| Lab exercise/Group work on A2 | ||
|
3.5 |
Lab exercise/Group work on A2 | |
| Decision trees; Random forest | ||
| Lab exercise/Group work on A2 | ||
|
3.6 |
Lab exercise/Group work on A2 | |
| Neural networks | ||
| Lab exercise/Group work on A2 | ||
|
3.7 |
Lab exercise/Group work on A2 | |
| Deep learning | Due A2 | |
| Lab exercise | ||
| 3.8 |
Discussion of feedback on assignments; Q&A | |
| 3.9 |
No lecture. Self study (prepare for the final exam) | |
| 3.10 | Final exam (Example questions; Results) | |
| 4.9 | Resit | |
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