The dataset belongs to a famous study on heart disease with around 4000 observations.
The approach is very basic: using Lazy Predict to classify with many models the risk of cardiovascular events. The best performing model is then automatically selected and implemented to do predictions. The main goal is to develop an automatic pipeline for training/testing a classifier, implementating the best performing model and putting it into production as a web app with minimum code and minimum effort.
The WebApp is obtained using Streamlit and can be reached at the following link: https://cardiovascular-disease-medical-treatment.streamlit.app/