Pattern Recognition and Machine Learning (Information Science and Statistics)
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Machine Learning: An Algorithmic Perspective (Chapman & Hall/Crc Machine Learning & Pattern Recognition)
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
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Pattern Classification (2nd Edition)
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Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning)
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Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
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Elements of Information Theory 2nd Edition (Wiley Series in Telecommunications and Signal Processing)
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Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
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Numerical Recipes 3rd Edition: The Art of Scientific Computing
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Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems
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Introduction to Machine Learning, Second Edition (Adaptive Computation and Machine Learning)
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Convex Optimization
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Introduction to Algorithms, Second Edition
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An Introduction to Information Theory
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Probability Theory: The Logic of Science (Vol 1)
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The Mathematical Theory of Communication
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Introduction To The Theory Of Neural Computation, Volume I (Santa Fe Institute Series)
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Information Theory and Statistics (Dover Books on Mathematics)
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The Elements of Statistical Learning
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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
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