MATH 470 Machine Learning Algorithms
Topics include dimension reduction, feature creation and extraction, kernel methods and smoothing, supervised learning techniques such as nearest neighbors and support vector machines, un-supervised learning techniques such as clustering, and cross-validation.
Prerequisite
A “C” or
better
in
class='sc-courselink' href='/en/2019-2020/2019-2020-academic-catalog/course-descriptions-undergraduate-and-graduate/math-mathematics/300/math-320'>MATH 320 and in class='sc-courselink' href='/en/2019-2020/2019-2020-academic-catalog/course-descriptions-undergraduate-and-graduate/cs-computing-sciences/100/cs-160'>CS 160 or CS 170
Notes
Three hours per week