Apache Spark Deep Learning Cookbook

Getting ready

In recurrent neural networks, the hidden state from the previous time step is fed back into the network at the next time step, as shown in the following diagram:

Basically, the upward facing arrows going into the network represent the inputs (matrices/vectors) to the RNN at each time step, while the upward-facing arrows coming out of the network represent the output of each RNN unit. The horizontal arrows indicate the transfer of information learned in a particular time step (by a particular neuron) onto the next time step.

More information about using RNNs can be found at : https://deeplearning4j.org/usingrnns