Title: Deep Learning, Author: Ian Goodfellow
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
Title: Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies, Author: John D. Kelleher
Title: Prediction, Learning, and Games, Author: Nicolo Cesa-Bianchi
Title: Optimal Learning / Edition 1, Author: Warren B. Powell
Title: Bayesian Reasoning and Machine Learning, Author: David Barber
Title: Scaling up Machine Learning: Parallel and Distributed Approaches, Author: Ron Bekkerman
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: Knowledge Discovery with Support Vector Machines / Edition 1, Author: Lutz H. Hamel
Title: Machine Learning: Discriminative and Generative / Edition 1, Author: Tony Jebara
Title: Learning from Data: Concepts, Theory, and Methods / Edition 2, Author: Vladimir Cherkassky
Title: Change of Representation and Inductive Bias / Edition 1, Author: D. Paul Benjamin
Title: Abductive Reasoning and Learning / Edition 1, Author: Dov M. Gabbay
Title: Advances In Pattern Recognition - Proceedings Of The 6th International Conference, Author: Pinakpani Pal
Title: Learning in Non-Stationary Environments: Methods and Applications / Edition 1, Author: Moamar Sayed-Mouchaweh
Title: Data Mining With Decision Trees: Theory And Applications, Author: Lior Rokach
Title: Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability / Edition 1, Author: Danilo P. Mandic
Title: Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning / Edition 1, Author: Te-Ming Huang

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