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MACHINE LEARNING

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MACHINE LEARNING

2017 Fall Term

3 Units

Computer Science 732

This course provides a broad introduction to machine learning and pattern recognition. Topics include but are not limited t Bayesian Inference, SVMs, Clustering and Classification, Decision Tress and Ensemble Methods. Particular focus will be place don the theoretical understanding of these methods, as well as their practical applications.

Other Requirements: PREREQ: ADMISSION TO GRADUATE PROGRAM IN COMPUTER SCIENCE

Class Schedule

Disclaimer

  • This schedule is informational and does not guarantee availability for registration.
  • Sections may be full or not open for registration. Please use WINS if you wish to register for a course.
Section Details Meeting Details & Topic Instructor Syllabus
 
01-LEC 3811
3 Units
09/06 - 12/22 (1) Th 5:00 PM - 7:30 PM
Lopamudra Mukherjee
MG0117MG0117

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