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 4-6pm (UK time). This will be in Huxley 202/206/210, with online support also available on Microsoft Teams. This arrangement is subject to change depending on the situation with COVID!
The live discussion/Q&A sessions will be held on Friday 4-5pm (UK time). This will be in Huxley 311, with online access (details to be announced). Again, this is subject to change! Keep your eyes peeled on Microsoft Teams and EdStem for announcements in case this changes!