A recurrent neural network is a form of neural network with a state/memory that runs on time series or sequential data. At each step a neural network uses the current state and input token to generate the next state and to predict the next token. As the hidden state is not part of the training data, the training phase is more complex than for a simple neural network.
Used in Chap. 14: pages 212, 213, 214, 218
Also known as RNN
Recurrent neural network (RNN)
Running a recurrent neural network on the data stream d1, d2, d3, ...