Title: Deep Learning, Author: Ian Goodfellow
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Title: Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies, Author: John D. Kelleher
Title: Bayesian Reasoning and Machine Learning, Author: David Barber
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: Learning with Uncertainty / Edition 1, Author: Xizhao Wang
Title: Applications of Learning Classifier Systems / Edition 1, Author: Larry Bull
Title: Machine Learning for Human Motion Analysis: Theory and Practice, Author: Liang Wang
Title: Design and Control of Intelligent Robotic Systems / Edition 1, Author: Dikai Liu
Title: Brain and Perception: Holonomy and Structure in Figural Processing / Edition 1, Author: Karl H. Pribram
Title: Phase Transitions in Machine Learning, Author: Lorenza Saitta
Title: Machine Learning and Image Interpretation / Edition 1, Author: Terry Caelli
Title: Machine Learning and Robot Perception / Edition 1, Author: Bruno Apolloni
Title: Reinforcement and Systemic Machine Learning for Decision Making / Edition 1, Author: Parag Kulkarni
Title: Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning / Edition 1, Author: Te-Ming Huang
Title: Pattern Classification Using Ensemble Methods, Author: Lior Rokach
Title: Algorithmic Learning in a Random World / Edition 1, Author: Vladimir Vovk

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