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.
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