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Recurrent Neural Networks (RNNs)

Data Science, Analytics and AI/ML

Recurrent Neural Networks are a class of neural networks designed to process sequential data by maintaining a hidden state that carries information from previous time steps to the current one. They were widely used by machine learning engineers and researchers for tasks like language modeling, speech recognition, and time-series forecasting before largely being supplanted by transformer architectures. Variants like LSTMs and GRUs were developed to address the vanishing gradient problem in long sequences.

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