Resources

Programming resources

• The R programming language: ggplot2
• Python resources: numpy, scipy, scikit-learn, matplotlib
• Java resources: Colt, Apache Commons Math

References

• Richard O. Duda, Peter E. Hart, David G. Stork, 2001. Pattern Classification (2nd ed)
• David Hand, Heikki Mannila, and Padhraic Smyth, 2001. Principles of Data Mining (link gives access to Cornellians; you may need to be coming from a Cornell IP address). Official book link at MIT Press here.
• Trevor Hastie, Robert Tibshirani, Jerome Friedman, 2009. The Elements of Statistical Learning, 2nd edition. Site includes full pdf, errata, R functions.
• John Hopcroft and Ravindran Kannan, draft of November 2014. Foundations of Data Science.
• Kevin Murphy, 2012. Machine Learning: A Probabilistic Perspective. MIT Press. (link gives access to Cornellians; you may need to be coming from a Cornell IP address).
• Pang-Ning Tan, Michael Steinbach, Vipin Kumar, 2006. Introduction to Data Mining. Site hosts slide sets and sample chapters.