Recurrent Neural networks (RNN) is a class of Artificial Neural network where connections between units form a directed cycle.

Recurrent Neural networks creates an internal state of the network which allows it to exhibit dynamic temporal behavior. (Machine Learning)

Unlike Feedforward Neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. This makes them applicable to tasks such as unsegmented connected handwriting recognition or speech recognition.

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