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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

Purpose of having the rule-based system

Generally, the rule-based system is used for developing NLP applications and generalized AI applications. There are bunch of questions that we need to answer to generate a clear picture about the rule-based system.

Why do we need the rule-based system?

The rule-based system tries to mimic human expert knowledge for the NLP applications. Here, we are going to address the factors that will help you to understand the purpose of the RB system:

  • Available corpus size is small
  • Output is too subjective
  • Easy for humans of a specific domain to generate some specialized rules
  • Difficult for machines to generate specialized rules by just observing small amounts of data
  • System output should be highly...
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