Download Some Books for Stat 602X

Some Books for Stat 602X
Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning,
by Alan J. Izenman, (2008), ISBN-10: 0387781889, ISBN-13: 978-0387781884, Springer.
Principles and Theory for Data Mining and Machine Learning, by Bertrand Clarke, Ernest
Fokoué, and Hao Helen Zhang, (2009), ISBN-10: 0387981349, ISBN-13: 978-0387981345,
Springer.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition,
by Trevor Hastie, Robert Tibshirani, and Jerome Friedman, (2009), ISBN-10: 0387848576,
ISBN-13: 978-0387848570, Springer.
Spline Models for Observational Data (CBMS-NSF Regional Conference Series in Applied
Mathematics), by Grace Wahba, (1990), ISBN-10: 0898712440, ISBN-13: 978-0898712445,
SIAM.
Pattern Recognition and Machine Learning, by Christopher M. Bishop, (2006), ISBN-10:
0387310738, ISBN-13: 978-0387310732, Springer.
Machine Learning: A Probabilistic Perspective, by Kevin P. Murphy, (2012), ISBN-978-0-26201802-9, MIT Press.
Foundations of Machine Learning, by Mehryar Mohri, Afshin Rostamizadeh, and Ameet
Talwalkar, (2012), ISBN-978-0-262-01825-8, MIT Press.
Learning From Data: A Short Course, by Yaser S. Abu-Mostafa, Malik Magdon-Ismail, and
Hsuan-Tien Lin, (2012), ISBN-10:600949-006-9, ISBN-13:978-1-60049-006-4, AMLbook.com.
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, by Ian Witten,
Eibe Frank, and Mark Hall, (2011), ISBN978-0-12-374856-0 (pbk.), Morgan Kaufmann.
The following is about classification only:
A Probabilistic Theory of Pattern Recognition, by Luc Devroye, László Györfi, and Gábor
Lugosi, (1996), ISBN-0-387-94618-7.