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Machine Learning I

(Elective Course)

Machine Learning I for IMC covers building, interpreting and applying predictive models used in marketing communications research. Students will explore many of the issues that arise in building such models, e.g., exploratory vs. confirmatory studies, inductive vs. deductive reasoning, multicollinearity, heteroscedasticity, nonlinearity, interactions, model selection, regularization, bias-variance tradeoff, extrapolation, and the curse of dimensionality. The course will help students understand how and why different methods work, which methods are well-suited for certain situations, and the extent of the conclusions that can be drawn from various models.