Practical Groups
Practicals will be held in weeks 4, 6, 7 and 8 in the Thom lab. The demonstrators for the practicals are Francisco Marmolejo (lead), Prince Abudu, Julia Camps, Javier Morales, Bernardo Pérez Orozco, Nikitas Rontsis, Wenjie Ruan and Bo Yang.
Group 1 | Thursday | 9h-11h | Francisco Marmolejo (lead) Julia Camps Javier Morales |
Group 2 | Thursday | 11h-13h | Francisco Marmolejo (lead) Javier Morales Nikitas Rontsis Bo Yang |
Group 3 | Fridays | 14h-16h | Francisco Marmolejo (lead) Prince Abudu Bernardo Pérez Orozco Nikitas Rontsis Wenjie Ruan |
Practicals
Submission Instructions
Your code and report will be evaluated by the instructors in the subsequent session, e.g. Week 4 will be evaluated in Week 6, and so on. We strongly recommend that you finish the actual work during the practical session itself and as far as possible try to get it evaluated during the same session, rather than wait until the following one. There will be no new practical in Week 8, you can finish off practical 3 if you don't complete it in Week 7. You should make every effort to get all practicals signed off before the end of your practical session in Week 8. However, in any case, the firm deadline to turn in your report for Practical 3 is Monday 12h00 of Week 9 at the CS reception.Lab Machine Instructions
In order to use the packages required please runmodule load Anaconda
on the shell before you begin. You may need to do this in every terminal that you open. Also when you use
jupyter notebook
please make sure you run this from a terminal on which you have run the previous command.
- Practical 1: [instructions] [white wine data] [red wine data]
- Practical 2: [instructions] [voting] [voting-full] [script]
- Practical 3: [instructions] [skeleton jupyter notebook] [html notebook]
Resources
For the practicals, we will use python 3.6 together with various machine learning related packages such as numpy, scipy, scikit-learn, matplotlib and tensorflow.
If you are unfamiliar with python, you may want to start here or go through the official tutorial. Using dir(.) and help(.) in ipython is a good way to learn as you start writing code. Then make sure you go through the numpy tutorial.
Please familiarise yourself with python and numpy before the first practical in Week 4.