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Natural Language Processing and Computational Linguistics

You're reading from   Natural Language Processing and Computational Linguistics A practical guide to text analysis with Python, Gensim, spaCy, and Keras

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788838535
Length 306 pages
Edition 1st Edition
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Author (1):
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Bhargav Srinivasa-Desikan Bhargav Srinivasa-Desikan
Author Profile Icon Bhargav Srinivasa-Desikan
Bhargav Srinivasa-Desikan
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Table of Contents (17) Chapters Close

Preface 1. What is Text Analysis? 2. Python Tips for Text Analysis FREE CHAPTER 3. spaCy's Language Models 4. Gensim – Vectorizing Text and Transformations and n-grams 5. POS-Tagging and Its Applications 6. NER-Tagging and Its Applications 7. Dependency Parsing 8. Topic Models 9. Advanced Topic Modeling 10. Clustering and Classifying Text 11. Similarity Queries and Summarization 12. Word2Vec, Doc2Vec, and Gensim 13. Deep Learning for Text 14. Keras and spaCy for Deep Learning 15. Sentiment Analysis and ChatBots 16. Other Books You May Enjoy

ChatBots

Getting a machine to learn to speak like a human being has been a holy grail for computer scientists as well as linguists of all the things which machines can mimic human behavior, holding a conversation has been a challenging ordeal. The quest to make such a machine which can chat with us humans (or a chatbot, if you will), has had many different approaches, and while none of them work perfectly, it is important to be aware of them - and pick and choose which kind will be the best for our purpose!

As for why we would want to build them chatbots are increasingly used by businesses; both to help customers to answer basic questions, as well as for building more complex personal assistants. It is also becoming increasingly easier to build such chatbots, and using open source tools.

There are many motivations to study the art of conversation for machines...

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