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Books:
 Bioinformatics: The machine learning approach - by P. Baldi and S. Brunak, MIT Press February 1998. 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. Includes an online appendix. Introduction to Machine Learning - By Nils J. Nilsson (downloadable draft) 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 each method, and reviews comparative trials in large-scale commercial and industrial problems. It makes accessible to a wide range of workers the complex issue of classification as approached through machine learning, statistics and neural networks, encouraging a cross-fertilization between these discplines. Machine Learning textbook - A textbook by Tom Mitchell, McGraw Hill, 1997. Reinforcement Learning: An Introduction - By Sutton and Barto, MIT Press, 1998. Support Vector Machines, Neural Networks and Fuzzy Logic Models - A textbook that provides an introduction to the field of learning from experimental data and soft computing.Suggested link
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War on Terrorism
Focus on the war on terrorism: September 11, 2001, Al-Qaida, US intervention in Afghanistan, military operations, news and media, human rights and liberties, international policy.
www.war-on-terrorism.info
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