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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

Understanding the basics of word2vec

Here, we will try to handle semantics at word level by using word2vec. Then, we will expand our concepts to paragraph level and document level. By looking at Figure 6.1, you will see the different kinds of semantics that we are going to cover in this book:

Figure 6.1: Different kinds of semantics

Semantics is a branch that deals with meaning in the area of NLP. We have already covered lexical semantic in Chapter 3, Understanding Structure of Sentences. So, here we will discuss more about distributional semantics. There are also other techniques or types in semantics, such as formal semantics compositional semantics; but right now, in this book, we are not going to cover these types or techniques.

Distributional semantics

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