DATA443
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Statistical Machine Learning
Subject
DATA - Data Science
Description
Core concepts of statistical machine learning, with an emphasis on the statistical background of the machine learning discipline. Classification and regression, nearest neighbours, Bayesian learning, decision tree, support vector machine, linear discriminant analysis, dimensionality reduction, and an introduction to neural networks.
Prerequisite(s): Data Science 335 and Computer Science 319.
Antirequisite(s): Credit for Data Science 443 and Computer Science 544 will not be allowed.
Prerequisite(s): Data Science 335 and Computer Science 319.
Antirequisite(s): Credit for Data Science 443 and Computer Science 544 will not be allowed.
Signature Learning
Research & Creative Scholarship
Course Attributes
Fee Rate Group(Domestic) - A, Fee Rate Group(International) -A, GFC Hours (3-2T), Research & Creative Scholarship - Related
Courses may consist of a Lecture, Lab, Tutorial, and/or Seminar. Students will be required to register in each component that is required for the course as indicated in the schedule of classes. Practicums, internships or other experiential learning modalities are typically indicated as a Lab component.
Component
LEC
Component
TUT
Units
3
Repeat for Credit
No
Subject code
DATA