About the book
This book is an introductory text on machine learning.
The style of the book is such that it can be used as a textbook
for an advanced undergraduate or graduate course,
at the same time aiming at interested academics and professionals
with a background in neighbouring disciplines. The material includes
necessary mathematical detail, but emphasises intuitions and how-to.
The challenge in writing an introductory machine learning text is to do
justice to the incredible richness of the machine learning field without
losing sight of the unifying principles.
One way in which this is achieved
in this book is by separate and extensive treatment of tasks and
features, both of which are common across any machine learning
approaches. Covering a wide range of logical, geometric and statistical
models, the book is one of the most comprehensive machine learning texts
around.
For excerpts and lecture slides click
here.
For the Table of Contents, see below.