COM S 578: Empirical Methods in Machine Learning and Data Mining

Cross-Listing: Not cross-listed.

This implementation-oriented course presents a broad introduction to current algorithms and approaches in machine learning, knowledge discovery, and data mining and their application to real-world learning and decision-making tasks. The course also covers experimental methods for comparing learning algorithms, for understanding and explaining their differences, and for exploring the conditions under which each is most appropriate.

Offered: Fall only

Prerequisites: CS280 and CS312, or the equivalent.

Grade options: Letter or S/U

Credit hours: 4

Recent offerings:

• http://www.cs.cornell.edu/courses/cs578/2007fa
  • Richard Caruana
• http://www.cs.cornell.edu/courses/cs578/2006fa
  • Richard Caruana
• http://www.cs.cornell.edu/courses/cs578/2005fa
  • Richard Caruana