This project explores three machine learning classifiers Decision Trees, Random Forest, and AdaBoost using the Bank Marketing dataset. I tuned each model using cross-validation and SMOTE to address class imbalance and evaluated them using ROC-AUC and PR-AUC metrics. The final report compares all models and sets the stage for future SVM exploration in Assignment 3.

This is a brief introduction to simple linear regression, with some examples of its use in R.

Analysis of the Adverse Health and Economic Impacts of US Storms

Incidences of reported bike theft in the City of Vancouver, according to the Vancouver Police Department. Map for GEOS372 class at UBC.