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Natural Language Processing with TensorFlow

You're reading from   Natural Language Processing with TensorFlow Teach language to machines using Python's deep learning library

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788478311
Length 472 pages
Edition 1st Edition
Languages
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Authors (2):
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Thushan Ganegedara Thushan Ganegedara
Author Profile Icon Thushan Ganegedara
Thushan Ganegedara
Motaz Saad Motaz Saad
Author Profile Icon Motaz Saad
Motaz Saad
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to Natural Language Processing FREE CHAPTER 2. Understanding TensorFlow 3. Word2vec – Learning Word Embeddings 4. Advanced Word2vec 5. Sentence Classification with Convolutional Neural Networks 6. Recurrent Neural Networks 7. Long Short-Term Memory Networks 8. Applications of LSTM – Generating Text 9. Applications of LSTM – Image Caption Generation 10. Sequence-to-Sequence Learning – Neural Machine Translation 11. Current Trends and the Future of Natural Language Processing A. Mathematical Foundations and Advanced TensorFlow Index

Other applications of Seq2Seq models – chatbots


One other popular application of sequence to sequence models is in creating chatbots. A chatbot is a computer program that is able to make a realistic conversation with a human. Such applications are very useful for companies with a huge customer base. Responding to the customers asking basic questions for which answers are obvious accounts for a significant portion of customer support requests. A chatbot can serve customers with basic concerns when it is able to find an answer. Also, if the chatbot is unable to answer a question, the request gets redirected to a human operator. Chatbots can save lot of the time that human operators spend answering basic concerns and let them attend to more difficult tasks.

Training a chatbot

So, how can we use a sequence-to-sequence model to train a chatbot? The answer is quite straightforward as we have already learned about the machine translation model. The only difference would be how the source and target...

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