CS 429 Introduction to Machine Learning
In-depth survey of basic and advanced concepts of machine learning. Topics include: linear discrimination, supervised, unsupervised, semi-supervised learning, multilayer perception, convolution neural networks, maximum-margin methods, Monte-Carlo, and reinforcement learning. Knowledge of linear algebra and vector calculus also recommended.
Credits
3
Cross Listed Courses
CS 529
Prerequisite
CS 305 with a grade of C- or better