A recurrent neural network (RNN) is a type of neural network that can process sequences of data. Unlike a traditional neural network, which takes a single input and produces a single output, an RNN can take a sequence of inputs and produce a sequence of outputs. This is because an RNN has a “memory” of the past inputs, allowing it to make decisions based on previous inputs.
For example, a language translation RNN might take a sentence in one language as input and output a translation in another language. It does this by taking each word in the input sentence and using its “memory” of past words to decide which words should be used in the output sentence.