A Recurrent Neural Network (RNN) is a type of neural network designed to process sequential or temporal data. Unlike conventional neural networks, RNNs have feedback connections that allow them to maintain internal states and process sequences of variable length. This makes them suitable for tasks such as machine translation, speech recognition, text generation, and time series modeling. RNNs are used in a variety of applications across fields such as natural language processing, computer vision, and bioinformatics.
Applications of RNNs
Natural Language Processing (NLP):
- Language modeling, text generation, machine translation, and sentiment analysis.
Speech Recognition:
- Speech-to-text transcription and command recognition systems.
Time Series:
- Financial data prediction, sales analysis, and weather forecasting.
Music Generation:
- Melody composition and sequence generation.
