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Recurrent Neural Networks (RNNs) are a type of neural network that utilize previous outputs as inputs to capture sequential dependencies, making them suitable for tasks like language modeling and time series forecasting. Unlike feedforward neural networks, RNNs maintain a hidden state to remember past information, though they face challenges like vanishing and exploding gradients. Variants such as Long Short-Term Memory (LSTM) and Bidirectional Neural Networks (BiNN) have been developed to address these iss

Author
dachinenishiva
Language
EN