Machine Learning and Adaptive Intelligence 2018

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Week 4

Basis functions [PDF Lecture slides][Jupyter Lecture slides]

Lab Class

The notebook for the lab class can be downloaded from here.

To obtain the lab class in jupyter notebook, first open the jupyter notebook. Then paste the following code into the ipython notebook 

import urllib.request
urllib.request.urlretrieve('https://raw.githubusercontent.com/lawrennd/mlai2018/master/week4.ipynb', 'week4.ipynb')

You should now be able to find the lab class by clicking File->Open on the jupyter notebook menu.

YouTube Videos

There is a YouTube video available of me giving this material at the Gaussian Process Road Show in Uganda. The first 25 minutes of the relevant video covers model selection, and then it leads into the video second below which introduces Bayesian modelling.

Reading

  • Sections 1.5-1.6 of Rogers and Girolami.
  • Sections 3.1-3.4 (pg 95-117) Although you haven’t covered the beta density yet.
  • Section 1.2.3 (pg 21-24) and 1.2.6 (start from just past eq 1.64 pg 30-32) of Bishop
  • Section 1.3 of Bishop (pg 32-33)