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CSC 5601 - Theory of Machine Learning4 lecture hours 0 lab hours 4 creditsCourse Description This course provides a broad introduction to machine learning. Theory of machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions, rather than following strictly static program instructions. Topic categories include decision boundaries, optimization, and both supervised and unsupervised methods. Students will apply the theory to implementing and evaluating machine learning algorithms with hands-on, tutorial-oriented laboratory exercises. Prereq: ((MTH 2130 and MTH 2340) or MTH 5810 ) and (CSC 2621 or CSC 5610 ) or instructor consent Note: This course is open to qualified undergraduate students. Course Learning Outcomes Upon successful completion of this course, the student will be able to:
Prerequisites by Topic
Coordinator Dr. John Bukowy |
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