Portfolio of course work for my Master's in Data Science.
This project aims to analyze trends in the Paycheck Protection Program and to generate predictive models based on demographics to predict the likelihood of receiving a loan.
Application of predictive models on a real data set of the obstetric medicine field and methods of interpretability on the previously fitted XGBoost model.
This project explores linear regression model selection in R using Best Subset Selection (BIC), stepwise methods with cross-validation, Ridge, and Lasso. Includes MSE evaluation on test data, multicollinearity analysis (VIF), and correlation insights for variable selection.
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