Diabetic Retinopathy is a diabetic realted disease that affects the retina of the eye. Millions around the world suffer from this disease.

Currently, diagnosis happens through the use of a technique called fundus photography, which involves photographing the rear of the eye. Medical screening for diabetic retinopathy occurs around the world, but is more difficult for people living in rural areas.

Using machine learning and computer vision, we attempt to automate the process of diagnosis, which currently is manually being performed doctors. Using an ensemble of B3 and B5 Efficientnets, we achieve a Quadratic Weighted Kappa score of 0.905775. In comparison, the winning solution on Kaggle achieved 0.93612.