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 | Evaluation 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 11am-1pm. These will be held on site, with all the labs on Level 2 available for your use (Huxley 202/206/219/221/225). The teaching assistants will most likely be lingering in the main labs (Huxley 219/202/206).
The live discussion/Q&A sessions will be held on Thursdays 10-11am. These will be held fully remotely on Microsoft Teams. If you are on campus, Huxley 145 is reserved for you to sit in, although no staff will be physically available in person.