CMPS 3240/6240 Introduction to Machine Learnings

CMPS 3240/6240 Introduction to Machine Learnings
Introduction to Machine Learnings
This course provides an introduction to the fundamental concepts of machine learning and statistical pattern recognition. In addition, several examples of applications will be described. The topics covered include generative/discriminative and parametric/non-parametric supervised learning, including neural networks; unsupervised learning, including clustering, dimensionality reduction and kernel methods; learning theory, including tradeoffs, large margins and VC theory; reinforcement learning, including criteria for optimality, brute force methods, value function methods and direct policy search; feedforward/feedback adaptive control, direct/indirect adaptive control methods; and various applications.
Pre-requistites: CMPS 1500, CMPS/MATH 2170.
credit hours: 3