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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

Natural language understanding

Let's learn about natural language understanding:

  • Natural language understanding (NLU) is considered the first component of NLP
  • NLU is considered an Artificial Intelligence-Hard (AI-Hard) problem or Artificial Intelligence-Complete (AI-Complete) problem
  • NLU is considered an AI-Hard problem because we are trying to make a computer as intelligent as a human
  • NLU is hard, but nowadays, tech giants and research communities are improvising traditional Machine Learning algorithms and applying various types of deep neural network that will help to achieve the goal (computers can also have the intelligence to process natural language (NL))
  • NLU is defined as the process of converting NL input into useful a representation by using computational linguistics tools
  • NLU requires the following analysis to convert NL into a useful representation:
    • Morphological...
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