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Deep Learning A-Z™: Recurrent Neural Networks (RNN) - LSTM Variations

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Kirill Eremenko

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.

Education
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© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z Ct-1 Image Source: colah.github.io Ct
© SuperDataScienceDeep Learning A-Z Image Source: colah.github.io Ct-1 Ct
© SuperDataScienceDeep Learning A-Z Image Source: colah.github.io Ct-1 Ct
© SuperDataScienceDeep Learning A-Z
© 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:

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