Actuarial Predictive Analytic I

Catalog description

This proposed 3-credit course will cover the usual topics in an introductory-level course in modern Data Science, including Statistical Learning. More specifically, the topics that will be covered are: Linear models (Validation, Resampling Methods, Model Selection and Regularization, Shrinkage, Dimension Reduction). Generalized Linear Models (Logistic and Probit Regression Models, Categorical and Count Response, Measures of Fit) Unsupervised Learning (Decision trees and Random Forests, Bootstrap, Bagging, Principal Components, Cluster Analysis)