Document Type
Syllabus
Description
Machine learning studies automatic methods of learning to make accurate predictions or useful decisions based on past observations. This course introduces theoretical machine learning, including mathematical models of machine learning, and the design and rigorous analysis of learning algorithms for classification, regression and ranking etc. Topics include: bounds on the number of random examples needed to learn; learning from non-random examples in the on-line learning model (for instance, for investment portfolio selection); how to boost the accuracy of a weak learning algorithm, kernel methods such as support-vector machines; consistency of machine learning methods.
Publication Date
Spring 2013
College
College of Engineering and Computer Science
Department
Computer Science
Course Number
CS 7900
Comments
Section 03 of CS7900: Information Security