MAT 4373 Statistical Machine Learning

3 units
Mathematics
Faculty of Science
Discriminant analysis, principal component analysis, support vector machines; reproducing kernel Hilbert spaces and kernel methods; neural networks; VC Theory; PAC learning. Additional topics may include: Bayesian modelling, manifold learning, boosting.

Components:

Lecture

Requirements:

Prerequisites: MAT 2122 , MAT 2371 , MAT 2375 , MAT 3373 .

Previously Offered Terms:

Winter

French Equivalent:

All Professors
A Average (9.158)
Most Common: A+ (53%)
19 students

P

S

NS

F

D

C

B

A-

A+

Maia Fraser

2 sections from Winter 2023 to Winter 2024

A+ Average (9.533)
Most Common: A+ (60%)
15 students

P

S

NS

F

D

C

B

A-

A+

Vincent Létourneau

Winter 2022 - C00

A- Average (7.750)
Most Common: A+ (25%)
4 students

P

S

NS

F

D

C

B

A-

A+