Currently, the recurrent neural network (RNN) is one of the most well-known and practical approaches used to construct deep neural networks. They are designed to process time-series data. Typically, data of this nature is found in the following tasks:
- Natural language text processing, such as text analysis and automatic translation
- Automatic speech recognition
- Video processing, for predicting the next frame based on previous frames, and for recognizing emotions
- Image processing, for generating image descriptions
- Time series analysis, for predicting fluctuations in exchange rates or company stock prices
In recurrent networks, communications between elements form a directed sequence. Thanks to this, it becomes possible to process a time series of events or sequential spatial chains. Unlike multilayer perceptrons, recurrent networks...
