On 07/19/2012 06:25 AM, Gael Varoquaux wrote:
On Thu, Jul 19, 2012 at 12:42:25AM +0200, federico vaggi wrote:
I was looking for suggestions for a good ML textbook - ideally one that has
a heavy emphasis on applications and is based on Python.
I don't know personally any that is based on Python. My favorite machine
learning book is 'The Elements of Statistical Learning'
http://www-stat.stanford.edu/~tibs/ElemStatLearn/
I would rather go with a very good book instead of one that emphasizes
on Python.
Many standard algorithms are in sklearn if you want to try them and I
don't feel
having some toy code adds much to the understanding.
I like both "The Elements of Statistical Learning" and Bishops book.
ESL has the advantage of being free. They have quite different
approaches. Bishop focuses a lot on the Bayesian viewpoint
while "Elements of statistical learning" focuses a lot on, well,
statistics. There is a heavy focus on linear models in ESL
and there are discussions about "Given this linear model fit,
is this input dimension significantly influencing the output."
By the way, metaoptimize <http://metaoptimize.com/qa> might be a better
place to ask this kind of question.
Cheers,
Andy
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