Recurrent Neural Network (RNN)

A Recurrent Neural Network (RNN) is a specialized class of artificial neural networks designed to process sequential data, unlike traditional feedforward networks that treat inputs independently. RNNs achieve this by maintaining an internal "memory" or hidden state that captures information from previous steps in the sequence, allowing past inputs to influence the processing of current and future inputs. This inherent ability to learn and remember context makes them particularly well-suited for tasks where the order and dependencies within data are crucial.