person Author: Process Fellows
Recurrent Neural Networks (RNNs) are designed to handle data that comes in a specific order — meaning the sequence of inputs is important. Such data can be continuous, like sound or video, but also structured, like text or even images.
Unlike simpler networks, RNNs don’t just process the current input; they also take into account what they have learned from previous steps. This gives them a kind of “memory” that allows them to recognize patterns over time. Because of this, RNNs are often used in applications such as speech recognition, language translation, time-series prediction, and image analysis.