(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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