September 2017
Beginner
244 pages
5h 20m
English
Both LSTM and GRU are capable of handling memory over long RNNs. However, a common question is which one to use? LSTM has been long preferred as the first choice for language models, which is evident from their extensive use in language translation, text generation, and sentiment classification. GRU has the distinct advantage of fewer trainable weights as compared to LSTM. It has been applied to tasks where LSTM has previously dominated. However, empirical studies show that neither approach outperforms the other in all tasks. Tuning model hyperparameters such as the dimensionality of the hidden units improves the predictions of both. A common rule of thumb is to use GRU in cases having less training data as ...