This course instructs students in the use probabilistic and statistical mathematics to develop computational models for the purpose of recognizing patterns in low-dimensional and high-dimensional spaces. Course topics include probability theory, introductory information theory, linear regression models, linear classifiers. Advanced topics in pattern recognition are also discussed and will vary each year.