MATH 308. Fundamentals of Statistical Learning.
Credits: 3
Offered by: Mathematics and Statistics (Faculty of Science)
This course is not offered this catalogue year.
Description
Theory and application of various techniques for the exploration and analysis of multivariate data: principal component analysis, correspondence analysis, and other visualization and dimensionality reduction techniques; supervised and unsupervised learning; linear discriminant analysis, and clustering techniques. Data applications using appropriate software.
- Prerequisite(s): MATH 208, one of MATH 223, MATH 236, MATH 247, MATH 251; MATH 323 or MATH 356.