Applied Predictive Analytics. 3 credits

Catalog description

Introduces predictive analytics and machine learning with applications in engineering, business, and econometrics. Topics include data preprocessing, predictive analytics with various machine learning models (e.g., linear, logistic regression, tree-based methods, SVM, neural networks, etc.) for regression and classification, time series analysis, and case studies. Provides a foundation of basic theory and methodology with applied examples to analyze large engineering, business, and econometric data for predictive decision making. Hands-on experiments with R will be emphasized. Offered by Systems Engr & Operations Rsch . May not be repeated for credit. Equivalent to SYST 568 .