Deep Learning A-Z™: Recurrent Neural Networks (RNN) - LSTM Variations
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This document discusses LSTM networks and their use in deep learning. It presents an overview of LSTM, a type of recurrent neural network, explaining how it addresses the vanishing gradient problem through its use of gates that allow information to flow without modification or get reset. The document also provides a link to a 2015 paper by Klaus Greff et al. that describes LSTMs and presents them as a search space for exploring computations beyond simple recurrence.
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Deep Learning A-Z™: Recurrent Neural Networks (RNN) - LSTM Variations
- 2. © SuperDataScienceDeep Learning A-Z Ct-1 Image Source: colah.github.io Ct
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- 6. © SuperDataScienceDeep Learning A-Z LSTM: A Search Space Odyssey By Klaus Greff et al. (2015) Link: https://arxiv.org/pdf/1503.04069.pdf Additional Reading: