Understanding Recurrent Neural Networks
A recurrent neural network (RNN) is a neural network that is made to process sequential data while being aware of the sequence of the data. Sequential data can involve time series based data and data that has a sequence but does not have a time component, such as text data. The applications of such a neural network are built upon the nature of the data itself. For time-series data, this can be either for nowcasting (predictions made for the current time with both past and present data) or forecasting targets. For text data, applications such as speech recognition and machine translation can utilize these neural networks.
Research in recurrent neural networks has slowed in the past few years with the advent of neural networks that can capture sequential data while removing recursive connections completely and achieving better performance, such as transformers. However, RNNs are still used extensively in the real world today to serve as a good...
