recurrent neural networks with attention
Recurrent neural networks with attention are a type of machine learning model that use both sequential processing and selective focus to improve performance on tasks involving sequential data. They dynamically emphasize different parts of the input sequence during processing, allowing the model to pay closer attention to relevant information and make more accurate predictions.
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