What are recurrent neural networks and how do they work?
An example of an AI chatbot conversation about understanding recurrent neural networks.
What are recurrent neural networks and how do they work?
Recurrent Neural Networks (RNNs) are a class of neural networks designed for sequential data. They use loops to allow information to persist.
What makes RNNs different from traditional neural networks?
Unlike traditional neural networks, RNNs can maintain a memory of previous inputs, making them suitable for tasks like language modeling.
Can you give me an example of where RNNs are used?
Sure! RNNs are commonly used in applications like speech recognition, language translation, and time series prediction.
What are some challenges associated with training RNNs?
Training RNNs can be challenging due to issues like vanishing gradients, which can make it hard for the network to learn long-term dependencies.
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