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Fundamentals, Techniques, and Applications, Introduction to Covariate Shift Adaptation, Support Vector Machines, Regularization, Optimization, and Beyond, International Affairs, History, & Political Science, Introduction to Machine Learning, Fourth Edition, Introduction to Natural Language Processing, Foundations of Machine Learning, Second Edition, Introduction to Machine Learning, Third Edition, Machine Learning in Non-Stationary Environments, Introduction to Machine Learning, Second Edition, Introduction to Statistical Relational Learning, Causation, Prediction, and Search, Second Edition, Graphical Models for Machine Learning and Digital Communication, Adaptive Computation and Machine Learning series. End-of-chapter exercises help readers to apply concepts learned. xxx+415 pages. The MIT Press, 2004. Introduction to Machine Learning, Fourth Edition (Adaptive Computation and Machine Learning) (Hardcover) By Ethem Alpaydin. 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