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CS 613 Machine Learning 3.0 Credits

This course studies modern statistical machine learning with emphasis on Bayesian modeling and inference. Covered topics include fundamentals of probabilities and decision theory, regression, classification, graphical models, mixture models, clustering, expectation maximization, hidden Markov models, Kalman filtering, and linear dynamical systems.

College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 571 [Min Grade: C] (Can be taken Concurrently)CS 520 [Min Grade: C] and CS 570 [Min Grade: C]

Peace Engineering

http://catalog.drexel.edu/graduate/collegeofengineering/peaceengineering/

...CS 520 , CS 570 , CS 571 (optional) Machine Learning and AI : CS 510 , CS 613...

Robotics and Autonomy

http://catalog.drexel.edu/graduate/collegeofengineering/roboticsandautonomy/

...3.0 Term Credits 9.0 Spring CS 613 Machine Learning 3.0 ECES 513...

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