Natural Language Processing with TensorFlow - Second Edition

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Recurrent Neural Networks

Recurrent Neural Networks (RNNs) are a special family of neural networks that are designed to cope with sequential data (that is, time-series data), such as stock market prices or a sequence of texts (for example, variable-length sentences). RNNs maintain a state variable that captures the various patterns present in sequential data; therefore, they are able to model sequential data. In comparison, conventional feed-forward neural networks do not have this ability unless the data is represented with a feature representation that captures the important patterns present in the sequence. However, coming up with such feature representations is extremely difficult. Another alternative for feed-forward models to model sequential ...