Textbooks:
These are books I either use regularly, refer to, have used excessively for a course,
or have read out of general interest (in the latter case, I list the book because I have enjoyed how it was written).
Pretty standard choices, for the most part.
Computer Vision
- Computer Vision: A Modern Approach - by David A. Forsyth and Jean Ponce
- Computer Vision: Algorithms and Applications - by Richard Szeliski
Machine Learning
- Pattern Recognition and Machine Learning - by Christopher M. Bishop
Natural Language Processing
- Speech and Language Processing - by Daniel Jurafsky and James H. Martin
Artificial Intelligence
- Artificial Intelligence: A Modern Approach - by Stuart Russell and Peter Norvig
Algorithms
- Introduction to Algorithms - by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein
- Algorithm Design - by Jon Kleinberg and Éva Tardos
Theory of Computation
- Introduction to the Theory of Computation - by Michael Sipser
Scientific Computing
- Scientific Computing: An Introductory Survey - by Michael T. Heath
Statistics
- Introduction to Probability Models - by Sheldon M. Ross
- Mathematical Statistics with Applications - by Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer
- Introduction to Time Series and Forecasting - by Peter J. Brockwell and Richard A. Davis
- A Modern Approach to Regression with R - by Simon Sheather
Other
- A Computational Perspective on Visual Attention - by John K. Tsotsos
Read my amazon review
- Programming Collective Intelligence - by Toby Segaran