Titlebook: Deep Learning for NLP and Speech Recognition; Uday Kamath,John Liu,James Whitaker Textbook 2019 Springer Nature Switzerland AG 2019 Deep L

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Susanne Rippl,Dirk Baier,Klaus Boehnke. This approach proved to be very effective for sentiment analysis, or more broadly text classification. One of the disadvantages of CNNs, however, is their inability to model contextual information over long sequences.

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Matteo Cesana,Alessandro E. C. Redondiortentous of these advances is the field of deep learning. Based on artificial neural networks that resemble those in the human brain, deep learning is a set of methods that permits computers to learn from data without human supervision and intervention. Furthermore, these methods can adapt to chang

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Peter Imbusch,Wilhelm Heitmeyer forms of convolutional and recurrent networks, respectively. When the data has certain dependencies such as out-of-order access, long-term dependencies, unordered access, most standard architectures discussed are not suitable. Let us consider a specific example from the bAbI dataset where there are

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