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http://www.p-value.info/2012/11/free-datascience-books.html

by Anon84 • 14 years ago

125 8 14 years ago

dbecker• 14 years ago

"Elements of Statistical Learning" should definitely be on the list. It is one of (if not THE) leading intro graduate textbooks in machine learning.

http://www-stat.stanford.edu/~tibs/ElemStatLearn/ or straight to the PDF at http://www.stanford.edu/~hastie/local.ftp/Springer/ESLII_pri...

gtani• 14 years ago

Also:

http://www-nlp.stanford.edu/IR-book/

https://www.ics.uci.edu/~welling/teaching/273ASpring10/Intro...

____________

more info on Barber book mentioned in OP: https://news.ycombinator.com/item?id=4672930

http://www.reddit.com/r/MachineLearning/comments/i06a0/book_...

mikevm• 14 years ago

Thanks! Do you happen to have the solutions manual for the IR book?

xaa• 14 years ago

ESL is a good book, but it should be mentioned that it is a significantly more difficult read than the other suggestions. Not at all an introductory-level text on ML.

disgruntledphd2• 14 years ago

Well, if you're willing to just follow the graphs and the argument the first time around, you can definitely get some use from it. I learned about classification, cross-validation and the bias-variance tradeoff from the first time I read it, and it significantly spurred me to deepen my understanding of the relevant mathematics.

andrewcooke• 14 years ago

for some reason the "bayesian reasoning and machine learning" (which to my eye is the most readable - perhaps because it is assumes the least from the reader) link is directly to the pdf. the site is at http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=... and includes a discount for the dead tree.

pwnna• 14 years ago

For the Mining of Massive Dataset book. Is the exercise solutions available somewhere?

orlandob• 14 years ago

wow, great resource. thanks.

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