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Python Natural Language Processing

You're reading from   Python Natural Language Processing Advanced machine learning and deep learning techniques for natural language processing

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787121423
Length 486 pages
Edition 1st Edition
Languages
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Author (1):
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Jalaj Thanaki Jalaj Thanaki
Author Profile Icon Jalaj Thanaki
Jalaj Thanaki
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Table of Contents (13) Chapters Close

Preface 1. Introduction FREE CHAPTER 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

In this chapter, we have looked at all kinds of preprocessing techniques which will be useful to you when you are developing an NLP system or an NLP application. We have also touched upon a spelling correction system which you can consider as part of the preprocessing technique because it will be useful for many of the NLP applications that you develop in the future. By the way, you can access the code on GitHub by clicking the following link: https://github.com/jalajthanaki/NLPython/tree/master/ch4

In the next chapter, we will look at the most important part for any NLP system: feature engineering. The performance of an NLP system mainly depends on what kind of data we provide to the NLP system. Feature engineering is an art and skill which you are going to adopt from the next chapter onwards and, trust me, it is the most important ingredient in developing the NLP systems...

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