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Tagged Works
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- Machine Learning: A Probabilistic Perspective by Kevin P. Murphy
- Scaling up Machine Learning: Parallel and Distributed Approaches by Ron Bekkerman
- Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing) by Isabelle Guyon
- Probabilistic Graphical Models: Principles and Techniques by Daphne Koller
- Introduction to Stochastic Search and Optimization by James C. Spall
- Mining Graph Data by Diane J. Cook
- Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data by Bing Liu
- Pattern Recognition and Machine Learning by Christopher M. Bishop
- First Look at Rigorous Probability Theory by Jeffrey S. Rosenthal
- Numerical Recipes 3rd Edition: The Art of Scientific Computing by William H. Press
- Pattern Classification (2nd Edition) by Richard O. Duda
- An Introduction to Support Vector Machines and Other Kernel-based Learning Methods by Nello Cristianini
- Foundations of Statistical Natural Language Processing by Christopher D. Manning
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie
- Machine Learning: A Guide to Current Research by Tom M. Mitchell
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