Introduction to Regression and Machine Learning for Analytics

Catalog description

Students learn about applied simple and multiple regression, regression models for supervised learning, correlation and collinearity, cost functions, model building, feature importance, logistic regression, and advanced methods for classification. The focus is on applications in business analytics.