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MATH 308. Fundamentals of Statistical Learning.

Credits: 3
Offered by: Mathematics and Statistics (Faculty of Science)
Terms offered: Winter 2027
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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.

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