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aayushbhaskar/MLND-Capstone-Diabetic-Retinopathy-Classification

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MLND-Capstone

To acquire the dataset please visit: : https://bit.ly/2Kimuvr

To see the benchmark solution please visit: https://www.kaggle.com/kmader/vgg16-640hr-nloss-retinopathy/code.

To read the article by Google cited in the proposal please visit: https://www.blog.google/topics/machine-learning/detecting-diabetic-eye-disease-machine-learning/.

The competiton hosted on Kaggle for DR detection: https://www.kaggle.com/c/diabetic-retinopathy-detection/.

Apart from the standard python libraries like numpy, os, sys, random etc, the other major libraries that I have used are tensorflow, for all the deep learning processing and model evaluation; and OpenCV, for preprocessing the images in the dataset. In addition to these two, I also have used tensorflow's tensorboard module to generate visuals for the project.Tensorboard for jupyter notebook can be easily installed by writing pip install jupyter-tensorboard on the terminal line.

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