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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

Developing something interesting

Here, we are going to train our word2vec model. The dataset that I'm going to use is text data of Game of Thrones. So, our formal goal is to develop word2vec to explore semantic similarities between the entities of A Song of Ice and Fire (from the show Game of Thrones). The good part is we are also doing visualization on top of that, to get a better understanding of the concept practically. The original code credit goes to Yuriy Guts. I have just created a code wrapper for better understanding.

I have used IPython notebook. Basic dependencies are gensim, scikit-learn, and nltk to train the word2vec model on the text data of Game of Thrones. You can find the code on this GitHub link:

https://github.com/jalajthanaki/NLPython/blob/master/ch6/gameofthrones2vec/gameofthrones2vec.ipynb.

The code contains inline comments and you can see the snippet...
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