What role do the hidden states in RNNs play in terms of sequential data processing?
- Storing Information Over Time
- Managing Data Loss
- Encoding Input Features
- Updating Weights for Classification
The hidden states in RNNs play a crucial role in storing information over time. They retain memory of past inputs and contribute to the model's ability to process sequential data, making them suitable for tasks with dependencies over time.
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