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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

Converting the word2vec model from black box to white box

From this section onwards, we are going to get an understanding of each of the components of the word2vec model, as well as the model's working process. So, in short, we are converting the black box part of word2vec into a white box.

We will focus on the following procedures in order to understand the word2vec model:

  • Distributional similarity based representation
  • Understanding the components of the word2vec model
  • Understanding the logic of the word2vec model
  • Understanding the algorithms and math behind the word2vec model
  • Some of the facts regarding the word2vec model
  • Application of the word2vec model

Let's begin!

Distributional similarity based representation

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