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Kaiming He committed Feb 6, 2016
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Expand Up @@ -86,3 +86,5 @@ Deep residual networks are very easy to implement and train. We recommend to see
https://github.com/apark263/cfmz
0. Torch, MNIST, 100 layers ([blog](https://deepmlblog.wordpress.com/2016/01/05/residual-networks-in-torch-mnist/)):
https://github.com/arunpatala/residual.mnist
0. A winning entry in Kaggle's right whale recognition challenge ([blog](http://blog.kaggle.com/2016/02/04/noaa-right-whale-recognition-winners-interview-2nd-place-felix-lau/)):
https://github.com/felixlaumon/kaggle-right-whale

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