Warm Up: Machine Learning with a Heart

Can you predict the presence or absence of heart disease in patients given basic medical information? This is the smallest, least complex dataset on DrivenData, and a great place to dive into the world of data science competitions. #health

beginner practice
oct 2019
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Predicting Heart Disease

We've all got to start somewhere. This is one of the smallest datasets on DrivenData. That makes it a great place to dive into the world of data science competitions. Get your heart thumping and try your hand at predicting heart disease.


Heart disease is the number one cause of death worldwide, so if you're looking to use data science for good you've come to the right place. To learn how to prevent heart disease we must first learn to reliably detect it.

Our dataset is from a study of heart disease that has been open to the public for many years. The study collects various measurements on patient health and cardiovascular statistics, and of course makes patient identities anonymous.

Competition End Date:

Oct. 30, 2019, 12:12 a.m.

This competition is for learning and exploring, so the deadline may be extended in the future.

Data is provided courtesy of the Cleveland Heart Disease Database via the UCI Machine Learning repository.

Aha, D., and Dennis Kibler. "Instance-based prediction of heart-disease presence with the Cleveland database." University of California 3.1 (1988): 3-2.

Images courtesy of pxhere and Flickr user Intel Free Press