Neural Turing Machines are a landmark architecture in the field of machine learning

Neural Turing Machines are a landmark architecture in the field of machine learning. A differentiable version of a classic model of computation designed by Alan Turing, NTMs open up the possibility of using machine learning to learn algorithms that can access an external memory. However, more so than many other popular deep learning architectures, NTMs are notoriously difficult to implement effectively. This presentation will provide an overview of the NTM architecture as well as tips and tricks for implementation using conventional machine learning frameworks. This presentation will also describe how NTMs can be used for standard machine learning tasks, and will touch on Dynamic Neural Computers, the followup architecture which was recently published in Nature.

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