Endorsements by famous people
This is an extraordinary and important book, generous with insight
and rich with detail in statistics, information theory, and
probabilistic modeling across a wide swathe of standard, creatively
original, and delightfully quirky topics. David MacKay is an
uncompromisingly lucid thinker, from whom students, faculty and
practitioners all can learn.
Zoubin Ghahramani and Peter Dayan
Gatsby Computational Neuroscience Unit, University College London.
An utterly original book that shows the connections between such disparate
fields as information theory and coding, inference, and statistical physics.
Dave Forney, M.I.T.
An instant classic, covering
everything from Shannon's fundamental theorems to the postmodern theory
of LDPC codes. You'll want two copies of this astonishing book,
one for the office and one for the fireside at home.
Bob McEliece, California Institute of Technology
Endorsements by users
I am involved
with teaching undergraduate information theory at Royal Holloway. We aim to make
this book a reference text in our related courses.
I have found the
book very enjoyable to read and I think that it is far easier for students
to relate to as the maths is explicit and easy to follow, with excellent
Congratulations on an inspirational
book! This is by far the best book I have read in years!
David Lindsay, Computer Learning Research Centre (www.clrc.rhul.ac.uk)
I am compelled to state categorically that this is one of the finest text
books I have read on these subjects. I have even pilfered some of the material
for use in my classes.
Samir Chettri, UMBC
One of the best technical books ever written,
period. It's a joy to read and students I have shown it to are attracted to it like bees
Alpan Raval, Keck Graduate Institute & Claremont Graduate University
A quite remarkable work to have come from
a single author ... the three topic areas of its title
actually fall short of indicating its full breadth of coverage.
This magnificent piece of work is valuable in introducing a
new integrated viewpoint, and it is clearly an admirable basis
for taught courses, as well as for self-study and reference.
Alex Andrew. Robotica 2004.
`... Without compromising mathematical rigor, MacKay manages to reach through the page to the reader, creating the impression that the student is across the desk from a friendly and supportive tutor.' -
Review by H. Van Dyke Parunak
`an academic gold mine ... The book's layout makes it easy for readers to
access whatever they are concerned with.'
- Review by Sylvain Piechowiak
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