Theming recognizing validating sequencing

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It is helpful to note the ‘recurrent’ property of the network, where the previous output for an input item becomes a part of the current input which comprises the current item in the sequence and the last output.

When done over and over, the last output would be the result of all the previous inputs and the last input.

You can read more about the utility of RNNs in Andrej Karpathy’s brilliant blog post.The purpose of this tutorial is to help anybody write their first RNN LSTM model without much background in Artificial Neural Networks or Machine Learning.The discussion is not centered around the theory or working of such networks but on writing code for solving a particular problem.The entire sequence is to be studied to determine the output.This is where Recurrent Neural Networks (RNNs) find their use.

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For example, for a neural net to identify the nouns in a sentence, having just the word as input is not helpful at all.

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