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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

This chapter gave you an introduction to NLP. You now have a brief idea about what kind of branches are involved in NLP and the various stages for building an expert system using NLP concepts. Lastly, we set up the environment for NLTK. All the installation guidelines and codes are available on GitHub.

In the next chapter, we will see what kind of corpus is used on NLP-related applications and what all the critical points we should keep in mind are when we analyze a corpus. We will deal with the different types of file formats and datasets. Let's explore this together!

You have been reading a chapter from
Python Natural Language Processing
Published in: Jul 2017
Publisher: Packt
ISBN-13: 9781787121423
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