SYS 6016

Machine Learning

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Course Description

Pre-Requisite(s): A course covering statistical techniques such as regression

A graduate-level course on machine learning techniques and applications with emphasis on their application to systems engineering. Topics include: Bayesian learning, evolutionary algorithms, instance-based learning, reinforcement learning, and neural networks. Students are required to have sufficient computational background to complete several substantive programming assignments. Co-Listed with CS 6316.


  • Laura Barnes

     Rating

     Difficulty

     GPA

    3.79

     Sections

    Last Taught

    Spring 2014

  • Abigail Flower

     Rating

     Difficulty

    4.00

     GPA

    3.70

     Sections

    Last Taught

    Spring 2017

  • Quanquan Gu

     Rating

     Difficulty

     GPA

    3.66

     Sections

    Last Taught

    Spring 2018

  • Abigail Brown

     Rating

     Difficulty

     GPA

     Sections

    Last Taught

    Spring 2018