Bioinformatics: The machine learning approach
by P. Baldi and S. Brunak, MIT Press February 1998.
http://www.cbs.dtu.dk/mitbook/mitbook.html
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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
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Introduction to Machine Learning
By Nils J. Nilsson (downloadable draft)
http://robotics.stanford.edu/people/nilsson/mlbook.html
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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
http://www.amsta.leeds.ac.uk/~charles/statlog/
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Machine Learning textbook
A textbook by Tom Mitchell, McGraw Hill, 1997.
http://www.cs.cmu.edu/~tom/mlbook.html
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Reinforcement Learning: An Introduction
by Sutton & Barto, MIT Press, 1998.
http://www-anw.cs.umass.edu/~rich/book/the-book.html
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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
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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
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