Machine Learning

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





Pattern Recognition and Machine Learning

By: Christopher M. Bishop

2006

Information Theory, Inference and Learning Algorithms

By: David J. C. MacKay

2003

Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond

By: Bernhard Schlkopf, Alexander J. Smola

2001

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

By: Nello Cristianini, John Shawe-Taylor

2000

Kernel Methods for Pattern Analysis

By: John Shawe-Taylor, Nello Cristianini

2004

Support Vector Machines

By: Ingo Steinwart, Andreas Christmann

2008

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

Introduction to Machine Learning

By: Ethem Alpaydin

2014

Machine Learning

By: Tom M. Mitchell

1997

Machine Learning: A Probabilistic Perspective

By: Kevin P. Murphy

2012

Reinforcement Learning: An Introduction

By: Richard S. Sutton, Andrew G. Barto

1998