Recurrent Neural Network
term_id: recurrent_neural_network
Category: basic_concepts
Definition
RNNs are designed to recognize patterns in sequences of data, such as text, genomes, handwriting, or spoken words. Unlike feedforward networks, they have internal memory that captures information about what has been processed so far. This makes them particularly effective for time-series prediction, natural language processing, and speech recognition tasks where context from previous steps is crucial.
Summary
An RNN is a class of artificial neural networks where connections between nodes form a directed graph along a temporal sequence.
Key Concepts
- Sequential Data
- Hidden State
- Temporal Dynamics
- Backpropagation Through Time
Use Cases
- Language Modeling
- Time Series Forecasting
- Speech Recognition