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May 12, 2024
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2023-2024 Graduate Catalog
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BIA 6303 - Predictive Models
(2)
The course examines advanced machine learning methods. Students learn to build, train, and validate predictive models. Topics include model tuning, regularization, support vector machines, ensemble models, neural nets, Bayesian analysis, Markov Chain Monte Carlo (MCMC) methods, and recommender systems. Emphasis is placed on working with large data sets and communicating results to diverse audiences. The primary software used is Python. Other topics and software may be incorporated.
Prerequisite: BIA 6301 .
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