Review:
Recurrent Neural Networks (rnns)
overall review score: 4.5
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score is between 0 and 5
Recurrent Neural Networks (RNNs) are a class of artificial neural networks where connections between nodes form directed cycles. This allows RNNs to exhibit dynamic temporal behavior and are commonly used in deep learning for sequential data processing tasks.
Key Features
- Ability to capture sequential dependencies
- Flexibility in input and output data types
- Suitable for natural language processing, time series analysis, and speech recognition
Pros
- Effective for tasks involving sequences of data
- Can handle variable length inputs
- Stateful memory allows retention of context
Cons
- Vanishing/exploding gradient problem that can affect training
- Limited ability to remember long-term dependencies