Mar 28, 2024  
2021-2022 Undergraduate Academic Catalog and Student Handbook 
    
2021-2022 Undergraduate Academic Catalog and Student Handbook [ARCHIVED CATALOG]

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STA 3241 - Statistical Learning


Credits: 3

Prerequisites: STA 3036 - Probability and Statistics for Business, Data Science, and Economics  or (MAS 3114 - Computational Linear Algebra  and STA 2023 - Statistics 1  ) 

 
Course Description: This is an introductory-level course in supervised learning. Topics include classification and regression, cross-validation and bootstrap, model selection, dimension reduction, tree-based methods, random forests and boosting, support-vector machines, principal components, and cluster analysis. Students will have hands-on experience in model building, machine learning, and implementation.



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