Machine Learning

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





Pattern Recognition and Machine Learning

By: Christopher M. Bishop

2006

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

By: Trevor Hastie, Robert Tibshirani, Jerome Friedman

2016

Deep Learning

By: Ian Goodfellow, Yoshua Bengio, Aaron Courville

2016

Foundations of Machine Learning

By: Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar

2012

Algorithms for Reinforcement Learning

By: Csaba Szepesvari, Ronald Brachman, Thomas Dietterich

2010

Reinforcement Learning: An Introduction

By: Richard S. Sutton, Andrew G. Barto

1998

Kernel Methods and Machine Learning

By: S. Y. Kung

2014

Digital Neural Networks

By: S.Y. Kung

2008

Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

By: John D. Kelleher, Brian Mac Namee, Aoife D'Arcy

2015