Rodney D. Nielsen
Research Scientist
Research Assistant Professor
Assistant Professor Adjunct
Boulder Language Technologies
University of Denver
University of Colorado at Boulder
CSCI 5622-002 Machine Learning, Fall 2009
Course Materials

Text: Tom Mitchell. (1997). Machine Learning. McGraw Hill.

Much of the course material isn’t covered in any single textbook. Additional readings will generally be assigned to address these topics.

Other books with relevant material include:

  • Bishop. (2007). Pattern Recognition and Machine Learning. Oxford University Press.
    (Provides a thorough probabilistic interpretation of many ML concepts.)
  • Duda, Hart and Stork. (2000). Pattern Classification. Wiley.
  • Hastie, Tibshirani and Friedman. (2009) The Elements of Statistical Learning. Springer
  • Kearns and Vazirani. (1994). Introduction to Computational Learning Theory. MIT Press.
  • Schölkopf and Smola. (2001). Learning with Kernels. MIT Press.
  • Shawe-Taylor and Crisianini. (2004). Kernel Methods for Pattern Analysis. Cambridge University Press.
  • Vapnik. (1998). Statistical Learning Theory. Wiley.
  • Witten and Frank. (2005). Data Mining. Morgan Kaufmann.
    (Very easy to read, practical view of some ML concepts and data mining issues.)

External readings, class notes and course assignments will be available from the course syllabus.