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Python Natural Language Processing

You're reading from  Python Natural Language Processing

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781787121423
Pages 486 pages
Edition 1st Edition
Languages
Toc

Table of Contents (13) Chapters close

Preface 1. Introduction 2. Practical Understanding of a Corpus and Dataset 3. Understanding the Structure of a Sentences 4. Preprocessing 5. Feature Engineering and NLP Algorithms 6. Advanced Feature Engineering and NLP Algorithms 7. Rule-Based System for NLP 8. Machine Learning for NLP Problems 9. Deep Learning for NLU and NLG Problems 10. Advanced Tools 11. How to Improve Your NLP Skills 12. Installation Guide

Summary

This chapter explored the basics of linguistics, which are often used to develop NLP applications. We have seen all kinds of analysis related to NL. We have seen word level analysis and larger context analysis. We have seen difference between some of the key concepts to resolve any confusion. After this chapter, you can identify which concepts of linguistics or tool is more interesting for you to use. Researchers can find the potential research area if they want to pursue research either in linguistics, computer linguistics or computer science with major in NLP.

In the next chapter, we will focus on practical and coding aspects and begin our journey to develop NLP applications. The next chapter is all about preprocessing the data, one of the basic but important steps in developing NLP applications. Preprocessing includes some of the concepts which we have described here...

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