CS 529 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.  Prior knowledge of data structures is required.  Knowledge of linear algebra and vector calculus also recommended.  Research project requiring an application of a machine learning techniques.