Week 6: Lab Class

Preparation

You need to start ipython notebook on your machine. For the DCS machines in the Edgar Allen building follow these instructions. Page Redirection If you are not redirected automatically, follow the here.

Once ipython has started copy and paste the following commands into a new notebook file.

import urllib
urllib.urlretrieve('https://github.com/SheffieldML/notebook/blob/master/lab_classes/machines_and_intelligence/MI_Lab_class.ipynb', 'MI_Lab_class.ipynb')

Once you've pasted them in press Shift-enter to download the notebook. If you return to the tab containing the IPython Dashboard the lab class should now be there to download.

Learning Outcomes Week 6

This lecture covers the following learning outcomes

Mapping the basic programming concepts into algorithms for machine learning.
- Ability to make small modifications to existing code to change an algorithm.
Be able to relate lines in a programming language to mathematical formulae.
- Understanding that the mathematical derivations we create can map to implementations in code.
- Understanding how mathematics is implemented as code, for example data structures like arrays can map to mathematical structures like vectors.
Understanding the particular needs when interacting with data: an environment that allows the display of the data. (e.g. IPython notebook).
Reinforcing the previous lectures' learning outcomes.

This document last modified Wednesday, 21-May-2014 05:40:57 UTC