A recurrent neural network (RNN) is a type of artificial neural network designed specifically for processing sequential data. Unlike traditional feedforward neural networks, which process data in a single forward pass and do not retain any memory, RNNs have a built-in feedback mechanism that allows them to maintain an internal memory or state. This memory enables RNNs to take into account not only the current input but also the previous information they have processed. Consequently, RNNs excel at tasks involving time-series data or sequences of varying lengths, as they can capture the dependencies and context among elements in the sequence.
Python TensorFlow Deep Learning Tips - How to build a Recurrent Neural Network, LSTM, GRU, SimpleRNN
Updated: Nov 30, 2023