Math

• Linear Algebra and Its Applications by Gilbert Strang (Cengage Learning)
  
• Convex Optimization by Stephen Boyd and Lieven Vendenberghe (Cambridge University Press)
  
• A First Course in Probability (Pearson) and Introduction to Probability Models (Academic Press) by Sheldon Ross
  
  

Coding

• R in a Nutshell by Joseph Adler (O’Reilly)
  
• Learning Python by Mark Lutz and David Ascher (O’Reilly)
  
• R for Everyone: Advanced Analytics and Graphics by Jared Lander (Addison-Wesley)
  
• The Art of R Programming: A Tour of Statistical Software Design by Norman Matloff (No Starch Press)
  
• Python for Data Analysis by Wes McKinney (O’Reilly)
  
  

Data Analysis and Statistical Inference

• Statistical Inference by George Casella and Roger L. Berger (Cengage Learning)
  
• Bayesian Data Analysis by Andrew Gelman, et al. (Chapman & Hall)
  
• Data Analysis Using Regression and Multilevel/Hierarchical Models by Andrew Gelman and Jennifer Hill (Cambridge University Press)
  
• Advanced Data Analysis from an Elementary Point of View by Cosma Shalizi (under contract with Cambridge University Press)
  
• The Elements of Statistical Learning: Data Mining, Inference and Prediction by Trevor Hastie, Robert Tibshirani, and Jerome Friedman (Springer)
  
  

Artificial Intelligence and Machine Learning

• Pattern Recognition and Machine Learning by Christopher Bishop (Springer)
  
• Bayesian Reasoning and Machine Learning by David Barber (Cambridge University Press)
  
• Programming Collective Intelligence by Toby Segaran (O’Reilly)
  
• Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig (Prentice Hall)