Prediction of Heart Attacks Cases using Machine Learning 

The goal of this project was to predict the risk of heart attacks using data from over 300,000 individuals collected in the 2015 BRFSS survey, using machine learning techniques, specifically Ridge Regression and Regularized Logistic Regression, to classify individuals as high or low risk.