AI

Here you can find lists of great AI books are or have been used to teach courses at MIT.





Artificial Intelligence

By: Winston

1992

Artificial Intelligence: A Modern Approach

By: Stuart J. Russell, Peter Norvig

2003

Robot Vision

By: Berthold Klaus Paul Horn

1986

Probabilistic Graphical Models: Principles and Techniques

By: Daphne Koller, Nir Friedman

2009

Information Theory, Inference and Learning Algorithms

By: David J. C. MacKay

2003

Probabilistic Networks and Expert Systems: Exact Computational Methods for Bayesian Networks

By: Robert G. Cowell, Philip Dawid, Steffen L. Lauritzen

2007

Bayesian Networks and Decision Graphs

By: Thomas Dyhre Nielsen, FINN VERNER JENSEN

2007

Exploring Artificial Intelligence in the New Millennium

By: Gerhard Lakemeyer, Bernhard Nebel

2002

Neural Networks for Pattern Recognition

By: Christopher M. Bishop

1996

Pattern Classification

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

2000

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

By: Trevor Hastie, Robert Tibshirani, Jerome Friedman

2016

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

By: Nello Cristianini, John Shawe-Taylor

2000

Neural Networks for Pattern Recognition

By: Christopher M. Bishop

1996

Netlab

By: Ian T. Nabney

2004