This course introduces pattern recognition methods and theory discussing topics such as feature extraction, statistical classification, neural networks, fuzzy logic, support vectors, linear discriminant analysis, principal component analysis, clustering, and unsupervised learning.
Students implement algorithms, apply methods to selected problems, and document findings.
Make sure to get "caught-up" on all of the entries on the class blog! Start early on your coding!