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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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Toc

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

Why do we need a corpus?

In any NLP application, we need data or corpus to building NLP tools and applications. A corpus is the most critical and basic building block of any NLP-related application. It provides us with quantitative data that is used to build NLP applications. We can also use some part of the data to test and challenge our ideas and intuitions about the language. Corpus plays a very big role in NLP applications. Challenges regarding creating a corpus for NLP applications are as follows:

  • Deciding the type of data we need in order to solve the problem statement
  • Availability of data
  • Quality of the data
  • Adequacy of the data in terms of amount

Now you may want to know the details of all the preceding questions; for that, I will take an example that can help you to understand all the previous points easily. Consider that you want to make an NLP tool that understands...

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