Title: Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies, Author: John D. Kelleher
Title: The Elements of Statistical Learning: Data Mining, Inference, and Prediction / Edition 2, Author: Trevor Hastie
Title: Pattern Recognition and Machine Learning / Edition 1, Author: Christopher M. Bishop
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Title: Bayesian Reasoning and Machine Learning, Author: David Barber
Title: Scaling up Machine Learning: Parallel and Distributed Approaches, Author: Ron Bekkerman
Title: Prediction, Learning, and Games, Author: Nicolo Cesa-Bianchi
Title: Kernel Methods for Pattern Analysis / Edition 1, Author: John Shawe-Taylor
Title: Bayesian Networks and Decision Graphs / Edition 2, Author: Thomas Dyhre Nielsen
Title: Geometric Computing for Perception Action Systems: Concepts, Algorithms, and Scientific Applications / Edition 1, Author: Eduardo Bayro Corrochano
Title: Learning from Data: Concepts, Theory, and Methods / Edition 2, Author: Vladimir Cherkassky
Title: Machine Learning for Human Motion Analysis: Theory and Practice, Author: Liang Wang
Title: Advances in Computational Intelligence and Learning: Methods and Applications / Edition 1, Author: Hans-Jïrgen Zimmermann
Title: Evolvable Machines: Theory & Practice / Edition 1, Author: Nadia Nedjah
Title: Tuning Metaheuristics: A Machine Learning Perspective / Edition 1, Author: Mauro Birattari
Title: Advances in Bayesian Networks / Edition 1, Author: José A. Gámez
Title: The Informational Complexity of Learning: Perspectives on Neural Networks and Generative Grammar / Edition 1, Author: Partha Niyogi
Title: Rough Sets and Data Mining: Analysis of Imprecise Data / Edition 1, Author: T.Y. Lin
Title: Computational Learning and Probabilistic Reasoning / Edition 1, Author: A. Gammerman
Title: Super-Intelligent Machines / Edition 1, Author: Bill Hibbard
Title: Automatic Learning Techniques in Power Systems / Edition 1, Author: Louis A. Wehenkel

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