Recurrent Neural Networks

Recurrent Neural Networks (RNNs) are a type of artificial intelligence model designed to process sequences of data, like sentences or time series. Unlike traditional neural networks, which analyze each piece of data independently, RNNs use their internal memory to remember previous inputs. This allows them to understand context and relationships over time, making them particularly effective for tasks like language translation, speech recognition, and predicting future events based on past data. Essentially, RNNs emulate a form of memory, enabling them to learn from sequences and make more informed decisions.