Are RNNs still the state-of-the-art for NLP?
No, Transformer models have mostly replaced RNNs because they process words in parallel, making training much faster.
Verify This Answer
Cross-check this information using these trusted sources:
More FAQs in What are Recurrent Neural Networks (RNN) and LSTM?
They are widely used for machine translation, speech-to-text, sentiment analysis, and time-series forecasting.
Due to vanishing gradients, the network forgets words at the beginning of a long sentence by the time it reaches the end.
The Cell State acts like a conveyor belt, allowing information to flow down the sequence with minimal modification.
Still have questions?
Browse all our FAQs or reach out to our support team