I was in Tom Mitchell's graduate machine learning class at CMU when he was
writing the book. We were working off of 'chapters in progress', but at
the time I thought what was there was great. It hits most of the major
topics in machine learning and gives algorithmic outlines of things in
pseudo code. Each topic section was enough to understand the higher level
concepts and then the references section pointed to the specifics. Again,
I thought it was a great survey book.
One side note, though, is that Mitchell isn't that hot on genetic
algorithms as a field of machine learning so those chapters weren't given
quite the same attention as the others (at least during the course).
One more side note, some of Mitchell's work at the time was on text
processing and classificiation on usenet and the web, so if you wanted to
check some of his papers they may be of interest to what you are doing.
-lee
On Fri, 6 Jul 2001, Ken Williams bestowed the following wisdom:
> [EMAIL PROTECTED] (Ken Williams) wrote:
> >You're right that there are a lot of resources to be found in a web
> >search, but most of it is about very specific applications - perhaps
> >introductory material is best found in a textbook.
>
> ...speaking of which, is anyone familiar with Thomas M. Mitchell's book
> "Machine Learning"? It has only positive reviews on Amazon, but I'm not
> sure whether that's reliable.
>
>
> ------------------- -------------------
> Ken Williams Last Bastion of Euclidity
> [EMAIL PROTECTED] The Math Forum
>
