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Related Questions
- What are the key mechanisms that enable RNNs to capture temporal dependencies in sequential data?
- How do RNNs utilize memory to retain information from previous time steps and use it to make predictions?
- What is the role of the activation function in RNNs, and how does it contribute to the learning process?
- Can you explain the concept of backpropagation through time (BPTT) and its significance in training RNNs?
- How do RNNs handle the vanishing gradient problem, and what are some techniques to mitigate this issue?
- What are some common applications of RNNs, and how do they perform in tasks such as language modeling and speech recognition?
- How do RNNs compare to other types of neural networks, such as CNNs and transformers, in terms of their ability to process sequential data?
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