Course notes - this is the student version
(containing gaps to be completed during the lectures), and will be
updated periodically as I finalise each chapter
The main recommended text book is Elements of
Statistical Learning, available freely on-line as a PDF. All
students should ensure that they have a copy available for
reference. However, 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 (2011/12), but should be more
relevant to those doing it next year (2012/13)
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.
