Skip to Content
Reinforcement Learning with TensorFlow
book

Reinforcement Learning with TensorFlow

by Sayon Dutta
April 2018
Intermediate to advanced content levelIntermediate to advanced
334 pages
10h 18m
English
Packt Publishing
Content preview from Reinforcement Learning with TensorFlow

Neural intra-attention model

This section explains the neural intra-attention model on the encoder-decoder network. Here,  represents the sequence of input (article) tokens, and  represents the sequence of output (summary) tokens. The encoder part of the network consists of bi-directional LSTM (see Appendix AFurther topics in Reinforcement Learning). Thus, the input sequence x is read using a bi-directional LSTM which computes the hidden states  from the embedding vectors of , where || represents concatenation of the vectors.

In the decoder ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Deep Learning with TensorFlow - Second Edition

Deep Learning with TensorFlow - Second Edition

Giancarlo Zaccone, Vihan Jain, Md. Rezaul Karim, Motaz Saad
Deep Learning with TensorFlow 2 and Keras - Second Edition

Deep Learning with TensorFlow 2 and Keras - Second Edition

Antonio Gulli, Dr. Amita Kapoor, Sujit Pal

Publisher Resources

ISBN: 9781788835725Supplemental Content