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Draft handbook for MSc Dissertation Projects, summer of 2016. Project proposals may or may not appear on the School blog

Course material for ID5059 Knowledge Discovery and Data Mining, Semester 2 of 2014-15. The coursework was co-developed with Carl Donovan.

Lecture notes



  • Tutorial 01 - Titanic Survival - zip file
  • Tutorial 02 - SVM with linear kernel - R code
  • Tutorial 02 - another SVM with linear kernel - R code
  • Tutorial 02 - SVM with radial kernel - R code

The Elements of Statistical Learning by Hastie, Tibshirani & Friedman is available from Stanford University. There are other useful resources at the same location, including sample R files.

R and Data Mining: Examples and Case Studies by Yanchang Zhao. This is the PDF of a textbook containing many worked examples (in R) together with detailed explanations of the theory and the the technicalities involved.

R material for non-geeks is available from the University of California at Davis.

As this appears not to be in the old examp paper repository, I've made available the 2010-20 MT5759 exam. Warning! Both the structure and content are likely to change this year; this document gives you some insight into the type of question set for Maths masters students.

Online R tutorials from Data Camp, Code School, and R Studio