Recurrent Neural Networks (RNNs) are a powerful type of neural network designed to handle sequences of data. Unlike traditional feedforward neural networks, RNNs have connections that form directed cycles, allowing them to persist information.
Key Features
- Ability to process sequences of variable length.
- Remember previous computations and use them for current processing.
- Effective for tasks like language modeling and time-series prediction.
Applications
RNNs are widely applied in speech recognition, language translation, and even generating text or music. 🌐🎶
How They Work
RNNs utilize their internal memory to process input sequences in a way that past inputs can inform future ones. This makes them particularly effective for tasks where context is crucial.