This is the code for this video on Youtube by Siraj Raval as part of the Deep Learning Nanodegree with Udacity. We're going to build a Differentiable Neural Computer capable of learning the mapping between binary inputs and outputs. The point of this demo is to break the DNC down to its bare essentials so we can really understand how the architecture works. This is the most complex network i've ever built. And it's dope AF.
run jupyter notebook in terminal to see the code pop up in your browser.
Install jupyter here
The credits for this code go to claymcleod. I've merely created a wrapper to get people started.