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Free eBooks On Machine Learning
- nocoment 13y agoDangerous links (Google ad network masquerading as downloads of the content.) First listing is from a commercial solver, rather sales oriented, though it looks like the topics may not depend on it?
- hbbio 13y agoInteresting. I didn't knew that the Hastie/Tibshirani/Friedman was legally available as a free download. I would recommend it to anyone with a sufficient maths/stats background.
- tom_b 13y agoYes, both 'The Elements of Statistical Learning' and 'An Introduction to Statistical Learning with Applications in R' are available free in pdf. For fans of hard copy, I recently found that if your local (university?) library is a SpringerLink customer, you can purchase a print-on-demand copy of either book for $26.99, which includes shipping. Interior pages are in black and white (including the graphs), but that is a really cheap price for these two. Andrew Ng's course notes from his physical class at Stanford (CS 229 - Machine Learning) are extensive and available as well at: http://cs229.stanford.edu/materials.html http://cs229.stanford.edu/materials.html
- etherealG 13y agoi'd suggest following prof ng's free online course instead, just finished it a few weeks ago and it's really good! https://class.coursera.org/ml-004/ https://class.coursera.org/ml-004/
- 11001 13y agoI'd suggest going back to the original youtube[1] and course materials[2]. Coursera version is nothing but a hand-wavy watered down "feel good" version of the original class. I also really like the Caltech's take "Learning from data"[3] [1] https://www.youtube.com/watch?v=UzxYlbK2c7E https://www.youtube.com/watch?v=UzxYlbK2c7E [2] http://cs229.stanford.edu/ http://cs229.stanford.edu/ [3] http://work.caltech.edu/telecourse.html http://work.caltech.edu/telecourse.html
- etherealG 13y agosorry but i disagree. the in video questions, the randomised problem sets, all the coursera stuff really helped me to learn the ideas.
- phoen 13y agoThe LION Way: Machine Learning plus Intelligent Optimization http://www.e-booksdirectory.com/details.php?ebook=9575 http://www.e-booksdirectory.com/details.php?ebook=9575 A Course in Machine Learning http://www.e-booksdirectory.com/details.php?ebook=9395 http://www.e-booksdirectory.com/details.php?ebook=9395 A First Encounter with Machine Learning http://www.e-booksdirectory.com/details.php?ebook=8818 http://www.e-booksdirectory.com/details.php?ebook=8818 Bayesian Reasoning and Machine Learning http://www.e-booksdirectory.com/details.php?ebook=5283 http://www.e-booksdirectory.com/details.php?ebook=5283 Introduction to Machine Learning http://www.e-booksdirectory.com/details.php?ebook=4493 http://www.e-booksdirectory.com/details.php?ebook=4493 The Elements of Statistical Learning: Data Mining, Inference, and Prediction http://www.e-booksdirectory.com/details.php?ebook=3267 http://www.e-booksdirectory.com/details.php?ebook=3267 Reinforcement Learning by C. Weber, M. Elshaw, N. M. Mayer http://www.e-booksdirectory.com/details.php?ebook=3227 http://www.e-booksdirectory.com/details.php?ebook=3227 Machine Learning by Abdelhamid Mellouk, Abdennacer Chebira http://www.e-booksdirectory.com/details.php?ebook=2852 http://www.e-booksdirectory.com/details.php?ebook=2852 How Are We To Know? by Nils J. Nilsson http://www.e-booksdirectory.com/details.php?ebook=2710 http://www.e-booksdirectory.com/details.php?ebook=2710 Reinforcement Learning: An Introduction http://www.e-booksdirectory.com/details.php?ebook=1825 http://www.e-booksdirectory.com/details.php?ebook=1825 Gaussian Processes for Machine Learning http://www.e-booksdirectory.com/details.php?ebook=1774 http://www.e-booksdirectory.com/details.php?ebook=1774 Machine Learning, Neural and Statistical Classification http://www.e-booksdirectory.com/details.php?ebook=1118 http://www.e-booksdirectory.com/details.php?ebook=1118 Introduction To Machine Learning http://www.e-booksdirectory.com/details.php?ebook=1117 http://www.e-booksdirectory.com/details.php?ebook=1117 Inductive Logic Programming: Techniques and Applications http://www.e-booksdirectory.com/details.php?ebook=1105 http://www.e-booksdirectory.com/details.php?ebook=1105 Practical Artificial Intelligence Programming in Java http://www.e-booksdirectory.com/details.php?ebook=32 http://www.e-booksdirectory.com/details.php?ebook=32 Information Theory, Inference, and Learning Algorithms http://www.e-booksdirectory.com/details.php?ebook=21 http://www.e-booksdirectory.com/details.php?ebook=21
- nichochar 13y agoFirst of all thanks for sharing. I would like to study machine learning. I have a good code and math background. Which of these books is the most recommended?
- snotrockets 13y ago"The Elements of Statistical Learning" is great. It assumes an astute reader, but if you've made it through some post-graduate level work, you'd be fine.
- hengheng 13y agoThe bad part about eBooks is that they always pile up. They are probably the most non-read books in existence. Or why should I bother reading 16 eBooks on the same topic, when reading a single good one would be the sane solution (the one I'd choose for paper books)?
- farresito 13y agoI certainly agree with you. Often, it's just better to buy a paper book than try to read a little bit here and there. After all, paper books are not that expensive. My personal problem is than I often buy books that I never end up reading, or that I read after years (five, six, or even more). I'm pretty sure I'm not the only one that suffers from this, though.
- nightski 13y agoActually there are several really good books in this list, also available as paper copies if you want (albeit quite expensive if you go that route. ESL for example is $70+). But I do agree, a good textbook is well worth the investment over some free poorly written one.
- adouzzy 13y agoebooks are brilliant as reference books. You can search and access them on multi devices almost every where.
- alleycat 13y agohttp://www.amazon.com/Programming-Collective-Intelligence-Building-Applications/dp/0596529325 http://www.amazon.com/Programming-Collective-Intelligence-Bu... I found this to be quite a good introduction.
- gautamnarula 13y agoI also have this book and highly recommend it.
- kurumo 13y agoWhile not free, 'Machine Learning: A Probabilistic Perspective' (http://www.amazon.co.uk/gp/aw/d/0262018020 http://www.amazon.co.uk/gp/aw/d/0262018020) is the best book I have found so far. I also second the recommendations for Tibshirani's and MacKay's books; the former for mathematical foundations, the latter for the intuition.