Course notes - this is the student version
(containing gaps to be completed during the lectures), and will be
updated periodically as I revise each chapter
The main recommended text book is Elements of
Statistical Learning, available freely on-line as a PDF. This book is a little technical and terse in
places, so students may find it helpful to augment this reference with
some more introductory material.
An R and S companion to multivariate statistics
is also useful, and should be available electronically to Newcastle
University students via the above "reading list" link. It proceeds at
a more gentle pace than the text above, and gives a bit more
background material.
Bayesian
reasoning and machine learning, by David Barber. This is another
excellent book, available freely on-line. It isn't so relevant to
people currently doing the course, but may be in future!
Notes:
There are plenty of on-line notes that will also provide additional
information and background. In particular,
The Matrix Cookbook is an invaluable source of
matrix facts and identities you may have forgotten, and many that you
didn't ever know!
APTS Statistical Computing - notes for a course
for first year statistics postgraduate students, by Simon Wood - Chapters 1 and 2 are especially
relevant to this module.
