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