GRU (Gated Recurrent Unit)

A Gated Recurrent Unit (GRU) is a type of neural network designed to understand sequences, like sentences or time series data. It intelligently decides what information to remember or forget over time using specialized "gates." These gates act like filters, helping the network focus on relevant details and ignore noise, which allows it to capture long-term dependencies more efficiently. GRUs are simpler than some other models but still effective in modeling complex sequential patterns, making them useful for tasks like language translation, speech recognition, and forecasting.