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 Home » Artificial Intelligence » Machine Learning » Publications » Books

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1 - Machine Learning textbook   A textbook by Tom Mitchell, McGraw Hill, 1997. http://www.cs.cmu.edu/~tom/mlbook.html   [more pages from this URL]     2 - Computational Methods in Molecular Biology   Edited by S. Salzberg, D. Searls, and S. Kasif. Elsevier Science, 1998. The book is largely devoted to machine learning approaches to molecular biology. The site includes an online appendix. http://www.cs.jhu.edu/~salzberg/compbio-book.html   [more pages from this URL]     3 - Reinforcement Learning: An Introduction   by Sutton & Barto, MIT Press, 1998. http://www-anw.cs.umass.edu/~rich/book/the-book.html   [more pages from this URL]     4 - Machine Learning, Neural and Statistical Classification   This book is based on the EC (ESPRIT) project StatLog which compare and evaluated a range of classification techniques, with an assessment of their merits, disadvantages and range of application. This integrated volume provides a concise introduction to e http://www.amsta.leeds.ac.uk/~charles/statlog/   [more pages from this URL]     5 - Bioinformatics: The machine learning approach   by P. Baldi and S. Brunak, MIT Press February 1998. http://www.cbs.dtu.dk/mitbook/mitbook.html   [more pages from this URL]     6 - Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids.   by R. Durbin, S.R. Eddy, A. Krogh, G.J. Mitchison. Focus is mainly on machine learning methods for alignment, phylogeny, and RNA structure analysis. http://www.binf.ku.dk/users/krogh/books.html   [more pages from this URL]     7 - Introduction to Machine Learning   By Nils J. Nilsson (downloadable draft) http://ai.stanford.edu/people/nilsson/mlbook.html   [more pages from this URL]     8 - Support Vector Machines, Neural Networks and Fuzzy Logic Models   A textbook that provides a thorough, comprehensive and unified introduction to the field of learning from experimental data and soft computing. http://support-vector.ws   [more pages from this URL]

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