In this project, we build a heart disease prediction model and make comparison between different methods, using a Heart Disease UCI data set. We then implement both traditional ML methods (Linear/Logistic Regression, Ridge/k-NN Classifier, SVM, Bayes, Decision Trees) and Deep Learning methods (MLP, Keras) to predict the presence/absence of heart disease.