Machine Learning

Here you can find lists of great Machine Learning books are or have been used to teach courses at UCLA.





Introduction to Machine Learning

By: Ethem Alpaydin

2015

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition

By: Trevor Hastie, Robert Tibshirani, Jerome Friedman

2016

Pattern Recognition and Machine Learning

By: Christopher M. Bishop

2006

Machine Learning: A Probabilistic Perspective

By: Kevin P. Murphy

2012

Understanding Machine Learning: From Theory to Algorithms

By: Shai Shalev-Shwartz, Shai Ben-David

2014

Pattern Classification

By: Richard O. Duda, Peter E. Hart, David G. Stork

2000

Computer Age Statistical Inference: Algorithms, Evidence, and Data Science

By: Bradley Efron, Trevor Hastie

2016

Information Theory, Inference and Learning Algorithms

By: David J. C. MacKay

2003