DS 6040

Bayesian Machine Learning

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Course Description

Bayesian inferential methods provide a foundation for machine learning under conditions of uncertainty. Bayesian machine learning techniques can help us to more effectively address the limits to our understanding of world problems. This class covers the major related techniques, including Bayesian inference, conjugate prior probabilities, naive Bayes classifiers, expectation maximization, Markov chain monte carlo, and variational inference. A course covering statistical techniques such as regression.


  • Teague Henry

     Rating

     Difficulty

     GPA

    3.98

     Sections

    Last Taught

    Fall 2024

  • Taylor Brown

     Rating

     Difficulty

     GPA

    3.47

     Sections

    Last Taught

    Summer 2025