Lab Class

Preparation

You need to start ipython notebook on your machine. For the DCS machines in the Edgar Allen building follow these instructions.

Starting the Lab

You can have a look at the notebook for this lecture on line here.

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

import urllib
urllib.urlretrieve('https://github.com/lawrennd/mi2013/blob/master/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.