EE4389W
EE 4389W - Introduction to Predictive Learning (3 Cr.) Writing Intensive
Electrical and Computer Engineering (11122)
TIOT - College of Science and Engineering
EE 4389W - Introduction to Predictive Learning (3 Cr.) Writing Intensive
Course description
Empirical inference and statistical learning. Classical statistical framework, model complexity control, Vapnik-Chervonenkis (VC) theoretical framework, philosophical perspective. Nonlinear methods. New types of inference. Application studies.
prereq: [3025, ECE student] or STAT 3022; computer programming or MATLAB or similar environment is recommended for ECE students
prereq: [3025, ECE student] or STAT 3022; computer programming or MATLAB or similar environment is recommended for ECE students
Minimum credits
3
Maximum credits
3
Is this course repeatable?
No
Grading basis
OPT - Student Option
Lecture
Fulfills the writing intensive requirement?
Yes
Typically offered term(s)
Fall Odd Year