Welcome to the material for the first half of the Machine Learning and Neural Networks module (MATH3431) at Durham University. These pages consist of relevant lecture notes will be updated as the course progresses.

I would recommend that you use the html version of these notes (they have been designed for use in this way), however, there is also a pdf version of these notes.

In this first half of the module (Michaelmas Term), we will be focusing on “Machine Learning” rather than “Neural Networks”. We will i) go over the fundamental concepts of Machine (Statistical) Learning, ii) study the classic linear models, iii) explore models beyond Linearity and finally iv) look into the simpler yet powerful tree-based models.

If you would like to contact me regarding any of the material in this course, then my email address is

Credits: Thanks to Dr Tahani Coolen-Maturi, Dr Samuel Jackson and Dr Emmanuel Ogundimu for their kindly providing the materials for this module contents.