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CPSC 340 Machine Learning and Data Mining

Models of algorithms for dimensionality reduction, nonlinear regression, classification, clustering and unsupervised learning; applications to computer graphics, computer games, bio-informatics, information retrieval, e-commerce, databases, computer vision and artificial intelligence.

This course is eligible for Credit/D/Fail grading. To determine whether you can take this course for Credit/D/Fail grading, visit the Credit/D/Fail website. You must register in the course before you can select the Credit/D/Fail grading option.

Credits: 3

Pre-reqs: One of MATH 152, MATH 221, MATH 223 and one of MATH 200, MATH 217, MATH 226, MATH 253, MATH 263 and one of STAT 200, STAT 203, STAT 241, STAT 251, COMM 291, ECON 325, ECON 327, PSYC 218, PSYC 278, PSYC 366, MATH 302, STAT 302, MATH 318, BIOL 300; and either (a) CPSC 221 or (b) all of CPSC 260, EECE 320 and one of CPSC 210, EECE 210, EECE 309.


Status Section Activity Term Interval Days Start Time End Time Comments
  CPSC 340 T1A Tutorial 1 Tue Thu 13:00 14:00
  CPSC 340 T1B Tutorial 1 Tue Thu 14:00 15:00
  CPSC 340 T1C Tutorial 1 Tue Thu 16:30 17:30
  CPSC 340 T1D Tutorial 1 Tue Thu 15:00 16:00