I followed the tutorial of neural stack in https://iamtrask.github.io/2016/02/25/deepminds-neural-stack-machine/. Its topic is "Learning to Transduce with Unbounded Memory", issued by Google DeepMind.
I roughly understood this proposed model (above website had easily explained!), but I have not read any other reference journals.
The last example of tutorial is making input sequence backward. However, I wondered why we just separate input sequence into words and reorder them backward using simple conditional loop? (And that would not be a neural network)
I mean why creating hidden layers and operating lots of equations just to make input sequence backward? Is there any advantage of using neural network?
I will read reference journals anyway. But for now, I just want to know the reason to use neural network, instead of programming with simple conditional loop; its advantages.