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CPSC 340 103 (Lecture)

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

Location: Vancouver

Term 1 (Sep 03, 2019 to Nov 29, 2019)

Cr/D/F Grading Change Dates

Last day to change between Credit/D/Fail and percentage grading (grading options cannot be changed after this date): September 17, 2019


Withdrawal Dates
Last day to withdraw without a W standing : September 17, 2019
Last day to withdraw with a W standing
(course cannot be dropped after this date) :
October 11, 2019

TermDay Start TimeEnd TimeBuildingRoom
1 Mon Wed Fri14:0015:00ChemistryD300
Instructor: SCHMIDT, MARK
Note: this section is full

Seat Summary
Total Seats Remaining:0
Currently Registered:89
General Seats Remaining:0
Restricted Seats Remaining*:0
    *These seats are reserved for students who meet one of the following sets of restrictions:
 
  1. in one of these programs: BCS -OR-
    with one of these specializations: ****BUCC,****BUCS,****COMI -OR-
    with one of these specializations: CHN CPSC,CMJ CPSC,HON CPSC,MAJ CPSC
-  Select one Tutorial from sections T1A, T1B, T1C, T1D, T1E, T1F, T1G, T1H, T1K, T1Z
-  GRAD students: If you wish to take introductory Machine Learning for graduate credit, you should register for 532M in term 1. If you wish to take introductory Machine Learning for undergrad credit, you should register for 340 in term 2. (The CPSC 340 seats in term 1 are reserved for undergrads to ensure that undergrads have an opportunity to take the course as well).

Book Summary :
Title Reqd/Opt/Rel Author ISB
Artificial Intelligence: A Modern Approach 3/E Required RUSSELL 9780136042594