CSI 5155 Machine Learning

3 units
Computer Science
Faculty of Engineering
Concepts, techniques, and algorithms in machine learning; representation, regularization and generalization; supervised learning; unsupervised learning; advanced methods such as support vector machines, online algorithms, neural networks, hidden Markov models, and Bayesian networks; curse of dimensionality and large-scale machine learning. Category T in course list. This course is equivalent to COMP 5116 at Carleton University.

Components:

Lecture

Requirements:

Courses CSI 5155 , DTO 5100 , DTO 5101 , ELG 5255 , IAI 5100 , IAI 5101 , MIA 5100 , SYS 5185 cannot be combined for units.

Previously Offered Terms:

Fall
Winter

French Equivalent:

All Professors
A Average (8.806)
Most Common: A+ (46%)
217 students

P

S

NS

F

D

C

B

A-

A+

Herna Viktor

4 sections from Winter 2019 to Winter 2024

A Average (8.857)
Most Common: A+ (46%)
203 students

P

S

NS

F

D

C

B

A-

A+

Unknown Professors

2 sections from Fall 2022 to Fall 2023

A- Average (8.071)
Most Common: A+ (36%)
14 students

P

S

NS

F

D

C

B

A-

A+