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Skin Cancer Classification

Supervised/Transfer learning model in PyTorch(fastai)

I built a supervised learning model in PyTorch using transfer learning with MobileNet and the fastai API. Through fastai, I was able to utilize cyclical learning rates, extended data augmentation for the unbalanced dataset (such as shear), custom weight decay in place of L2 regularization, learning rate find and more. By using the depth-wise separable convolutions of MobileNet, I ended up with a memory efficient model and my results topped the charts from the 2018 competition.

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