Comments on: Learning, Machine Learning http://fseoane.net/blog/2009/learning-machine-learning/ Fri, 30 Jul 2010 21:06:18 +0000 http://wordpress.org/?v=2.2.2 By: Henry Oglesby http://fseoane.net/blog/2009/learning-machine-learning/#comment-33999 Henry Oglesby Thu, 08 Apr 2010 13:59:56 +0000 http://fseoane.net/blog/2009/learning-machine-learning/#comment-33999 The internet show many sites in your list, but this<a href="http://www.mentalidade.com/video-de-musica-do-filme-de-hannah-montana-miley-cyrus" rel="nofollow"> site </A>is very good between all. The internet show many sites in your list, but this site is very good between all.

]]> By: Yaroslav Halchenko http://fseoane.net/blog/2009/learning-machine-learning/#comment-32111 Yaroslav Halchenko Sun, 24 Jan 2010 03:02:47 +0000 http://fseoane.net/blog/2009/learning-machine-learning/#comment-32111 doh -- forgotten to mention url http://www-stat.stanford.edu/~tibs/ElemStatLearn/ doh — forgotten to mention url

http://www-stat.stanford.edu/~tibs/ElemStatLearn/

]]> By: Yaroslav Halchenko http://fseoane.net/blog/2009/learning-machine-learning/#comment-32110 Yaroslav Halchenko Sun, 24 Jan 2010 03:02:16 +0000 http://fseoane.net/blog/2009/learning-machine-learning/#comment-32110 wow -- I am surprised -- no one yet has mentioned The Elements of Statistical Learning: Data Mining, Inference, and Prediction. from Hastie/Tibshirani/Friedman * authors are quite well known in statistics and machine learning, expose many of their new algorithms in free software implementations (R) * book is nicely written and composed with good coverage of many methods * you can download complete book in PDF for FREE (legally). wow — I am surprised — no one yet has mentioned

The Elements of
Statistical Learning:

Data Mining, Inference, and Prediction.

from Hastie/Tibshirani/Friedman

* authors are quite well known in statistics and machine learning, expose many of their new algorithms in free software implementations (R)
* book is nicely written and composed with good coverage of many methods
* you can download complete book in PDF for FREE (legally).

]]> By: fabian http://fseoane.net/blog/2009/learning-machine-learning/#comment-31846 fabian Mon, 11 Jan 2010 08:30:44 +0000 http://fseoane.net/blog/2009/learning-machine-learning/#comment-31846 Thanks to all for your comments. I got a copy of Bishop's book and indeed I find it a great book. Specially useful are the solutions to the exercises that you can find on the web, specially if you use the book for self-study, like in my case. Thanks to all for your comments. I got a copy of Bishop’s book and indeed I find it a great book. Specially useful are the solutions to the exercises that you can find on the web, specially if you use the book for self-study, like in my case.

]]> By: timv http://fseoane.net/blog/2009/learning-machine-learning/#comment-31814 timv Sat, 09 Jan 2010 23:19:19 +0000 http://fseoane.net/blog/2009/learning-machine-learning/#comment-31814 I second the notion for Chris Bishop's book. What type of Machine Learning are you interested in doing? If you are interested in Graphical Models you should definitely check out <a href="http://www.amazon.com/Probabilistic-Graphical-Models-Principles-Computation/dp/0262013193" rel="nofollow">Daphne Koller and Nir Friedman brand new book</a>. I second the notion for Chris Bishop’s book. What type of Machine Learning are you interested in doing? If you are interested in Graphical Models you should definitely check out Daphne Koller and Nir Friedman brand new book.

]]> By: koala http://fseoane.net/blog/2009/learning-machine-learning/#comment-31811 koala Sat, 09 Jan 2010 21:35:27 +0000 http://fseoane.net/blog/2009/learning-machine-learning/#comment-31811 I recommend Introduction to Machine Learning by Ethem Alpaydin. I recommend Introduction to Machine Learning by Ethem Alpaydin.

]]> By: chris http://fseoane.net/blog/2009/learning-machine-learning/#comment-31806 chris Sat, 09 Jan 2010 10:46:29 +0000 http://fseoane.net/blog/2009/learning-machine-learning/#comment-31806 You might also want to check out the website mloss.org, which is trying to establish a software hub for machine learning. In terms of getting inspiration for implementations of ML algorithms, this is the right place to start (also it might help you in avoiding to reinvent the wheel). You might also want to check out the website mloss.org, which is trying to establish a software hub for machine learning.

In terms of getting inspiration for implementations of ML algorithms, this is the right place to start (also it might help you in avoiding to reinvent the wheel).

]]> By: Hoa Flinn http://fseoane.net/blog/2009/learning-machine-learning/#comment-31784 Hoa Flinn Fri, 08 Jan 2010 00:30:29 +0000 http://fseoane.net/blog/2009/learning-machine-learning/#comment-31784 Bonjour ŕ tous ! J'ai trouvé un service super pour ceux qui ne sont pas trop amis avec le webmastering ;-) Bonjour ŕ tous ! J’ai trouvé un service super pour ceux qui ne sont pas trop amis avec le webmastering ;-)

]]> By: Marcus http://fseoane.net/blog/2009/learning-machine-learning/#comment-31430 Marcus Sat, 19 Dec 2009 10:42:06 +0000 http://fseoane.net/blog/2009/learning-machine-learning/#comment-31430 You may want to look at Pieter Spronck's work on AI: http://ticc.uvt.nl/~pspronck/publications.html. The dynamic scripting patterns are very interesting for automated machine learning and conditional behaviour models. You may want to look at Pieter Spronck’s work on AI: http://ticc.uvt.nl/~pspronck/publications.html. The dynamic scripting patterns are very interesting for automated machine learning and conditional behaviour models.

]]> By: Asim Ansari http://fseoane.net/blog/2009/learning-machine-learning/#comment-31401 Asim Ansari Thu, 17 Dec 2009 17:31:20 +0000 http://fseoane.net/blog/2009/learning-machine-learning/#comment-31401 You may want to check out Pattern Recognition and Machine Learning by Christopher M Bishop. It is an excellent treatment of the subject. You may want to check out

Pattern Recognition and Machine Learning by Christopher M Bishop. It is an excellent treatment of the subject.

]]>