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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

Comparing the rule-based approach with other approaches

The rule-based approach is a very reliable engine which provides your application with high accuracy. When you compare the RB approach with ML approaches or deep learning approaches, you will find the following points:

  • For the RB approach, you need a domain expert, while for the ML approach, or for the deep learning approach, you don't need a domain expert
  • The RB system doesn't need a large amount of data, whereas ML and deep learning need a very large amount of data
  • For the RB system, you need to find patterns manually, whereas ML and deep learning techniques find patterns on your behalf as per the data and input features
  • The RB system is often a good approach for developing the first cut of your end product, which is still popular in practice
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