GRU

A Gated Recurrent Unit (GRU) is a type of artificial neural network designed to process sequential data, like sentences or time series. It efficiently remembers important information over time while discarding less relevant details. GRUs have internal "gates" that control what information to keep or forget, helping them capture long-term dependencies better than simpler models. They are commonly used in tasks such as language translation, speech recognition, and predicting sequences, because they can adaptively manage the flow of information throughout a sequence, making them powerful for understanding patterns that unfold over time.