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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

Deep learning techniques and NLG

In this section, we are going build a very simple but intuitive application for NLG. We are going to generate a one-line summary from shot articles. We will see all the details about summarization in this section.

This application took a lot of training time so you can put your model to train on CPU and meanwhile, you can do some other task. If you don't have any other task, then let me give you one.

Exercise

Try to figure out how you can generate a Wikipedia article by just providing some starting character sequences. Don't take me wrong! I'm serious! You seriously need to think on this. This is the dataset that you can use: https://einstein.ai/research/the-wikitext-long-term...

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