(scroll down to check the course calendar)
| Week | Topic/Activity | Assignment |
|
3.1 |
Introduction | |
| Linear regression; Gradient descent | Start A1 | |
|
3.2 |
Clustering; Nearest neighbor classification | |
| Lab exercise/Group work on A1 | ||
|
3.3 |
Bayesian classification; Logistic regression | |
| Lab exercise/Group work on A1 | ||
|
3.4 |
Support vector machine | Due A1; Start A2; Start project |
| Lab exercise/Group work on A2 | ||
|
3.5 |
Decision trees; Random forest | |
| Lab exercise/Group work on A2 | ||
|
3.6 |
Neural networks | |
| Lab exercise/Group work on A2 | ||
|
3.7 |
Convolutional neural networks | Due A2 |
| Guest lecture | ||
| 3.8 |
Work on project; Q&A | |
| 3.9 |
No lecture (work on project) | Due project |
| 3.10 | Project presentation (scheduled as "exam" on MyTimeTable) | |
| 4.9 | Resit |
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