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RNN Unit3 by SACHIN SAINI is a document available to read on EtoBox.

Recurrent Neural Networks (RNNs) are designed to process sequential data by maintaining a memory of previous inputs, allowing them to predict future outputs based on context. Key components include recurrent neurons that hold hidden states and the unfolding process that enables backpropagation through time (BPTT) for learning dependencies. RNNs are widely used in applications like text prediction, speech recognition, and machine translation, but face challenges such as vanishing gradients and difficulty cap

Author

SACHIN SAINI

Language

EN