CSCI5521
CSCI 5521 - Machine Learning Fundamentals (3 Cr.) Online may be available
Computer Science and Engineering Administration (11108)
TIOT - College of Science and Engineering
CSCI 5521 - Machine Learning Fundamentals (3 Cr.) Online may be available
Course description
Problem formulations and concepts of generalization, overfitting/under-fitting and model selection. Statistical foundations: maximum likelihood, maximum a posteriori, Expectation Maximization (EM), Bayesian estimation, and non parametric methods. Mathematical foundations and optimization: gradient descent, back propagation, regularization, quadratic programming. Perceptrons, neural networks and deep learning methods. Kernel methods and Support Vector Machines (SVMs). Machine Learning ethics.
prereq: STAT 3021, (CSci 2033 or Math 2142 or Math 4242)
prereq: STAT 3021, (CSci 2033 or Math 2142 or Math 4242)
Minimum credits
3
Maximum credits
3
Is this course repeatable?
No
Grading basis
OPT - Student Option
Lecture
Requirements
013022
Typically offered term(s)
Periodic Fall