DATA 436 Learning from Data Building on the frameworks introduced in IS 432, this course reviews a wide variety of machine learning techniques used for building and refining models for decision making. Support Vector Machines are introduced and a variety of Kernel based learning approaches are explored. Credits: 4 Prerequisite: DATA 101 and DATA 432 and MTH 308 , each with a grade of C or better or consent of instructor Satisfactory Grading: Ineligible for the Satisfactory/No Credit grade mode.
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