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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? FREE CHAPTER 2. Python Tips for Text Analysis 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

Summary

With the knowledge of the functions and strategies we have discussed, our text analysis can be aided; it is often when we are doing large scale text analysis that a small error can lead to completely nonsense results (remember garbage in, garbage out from Chapter 1, What is Text Analysis?).

We finish this mini-chapter with a few useful links on basic text manipulation:

  1. Printing and Manipulating Text [9]: Basic manipulation and printing of text, recommended if interested in how to display text in different ways.
  2. Manipulating Strings [10]: Basic String functions as well as exercises, useful for the further practice of string manipulation.
  3. Manipulating Strings in Python [11]: Similar to the two-preceding links includes a section on escape sequences as well.
  4. Text Processing in Python (book) [12]: Unlike the other links, this is a whole book. It covers the very fundamentals...
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