Programming Collective Intelligence: Building Smart Web 2.0 Applications
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Introduction to Algorithms
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Artificial Intelligence: A Modern Approach (2nd Edition) (Prentice Hall Series in Artificial Intelligence)
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Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)
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All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics)
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Probability Theory: The Logic of Science
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Computer Manual in MATLAB to Accompany Pattern Classification, Second Edition
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The Elements of Statistical Learning
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Semi-Supervised Learning (Adaptive Computation and Machine Learning)
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Causality: Models, Reasoning, and Inference
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Pattern Classification (2nd Edition)
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Machine Learning
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Introduction to Machine Learning (Adaptive Computation and Machine Learning)
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An Introduction to Bioinformatics Algorithms (Computational Molecular Biology)
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Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
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All of Nonparametric Statistics (Springer Texts in Statistics)
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Elements of Information Theory
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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
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Kernel Methods for Pattern Analysis
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Learning Bayesian Networks (Artificial Intelligence)
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Machine Learning (Mcgraw-Hill International Edit)
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Information Theory, Inference & Learning Algorithms
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Robust Statistics: Theory and Methods (Wiley Series in Probability and Statistics)
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Prediction, Learning, and Games
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