Course structure
Our course is structured as follows. A more detailed version can be found on the home page.
| Week | Topic | Lab | CW |
|---|---|---|---|
| 2 | Machine Learning: The Big Picture | LAB | - |
| 3 | K Nearest Neighbours and Decision Trees | LAB | CW1 |
| 4 | Evalation of Machine Learning systems | LAB | CW1 |
| 5 | Neural Networks (Part 1) | LAB | CW1 |
| 6 | Neural Networks (Part 2) | LAB | CW2 |
| 7 | Unsupervised Learning: Clustering & Density Estimation | LAB | CW2 |
| 8 | Evolutionary Algorithms | LAB | CW2 |
The lab sessions will be held on Tuesdays 2-4pm. These will be in Huxley 202/206.
The live discussion/Q&A sessions will be held on Thursdays 2-3pm. These will be in Huxley 308.