I own that book and can also recommend it.
- George

On 7/23/07, Łukasz Lew <[EMAIL PROTECTED]> wrote:

Absolutely the best book I've seen is:

Christopher M. Bishop
"Pattern Recognition and Machine Learning"

It's totally awesome!

Strong points:
- It have both Bayesian and non Bayesian ways explained
- the explanation is clear
- figures are so helpful (and aesthetic)
- it concentrates on prediction and classification and have
algorithmic perspective
   (contrary to MacKay's book)

There is a free chapter on graphical models:
http://research.microsoft.com/~cmbishop/PRML/Bishop-PRML-sample.pdf

Lukasz Lew

On 7/23/07, chrilly <[EMAIL PROTECTED]> wrote:
> I have a Phd in statistics. But Bayesian methods were at that time a
> non-topic. I know the general principles, but I want to learn a little
bit
> more about the latest developments in the field. Bayes is now chic,
there
> are many books about it. I assume also a lot of bad ones.
> Can anyone recommend me a good state of the art book about Bayesian
> inference. Should be somewhat in the applied direction, but also with a
> sound mathematical background.
>
> Chrilly
>
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> computer-go@computer-go.org
> http://www.computer-go.org/mailman/listinfo/computer-go/
>
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