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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

What you need for this book

Let's discuss some prerequisites for this book. Don't worry, it's not math or statistics, just basic Python coding syntax is all you need to know. Apart from that, you need Python 2.7.X or Python 3.5.X installed on your computer; I recommend using any Linux operating system as well.

The list of Python dependencies can be found at GitHub repository at https://github.com/jalajthanaki/NLPython/blob/master/pip-requirements.txt.

Now let's look at the hardware required for this book. A computer with 4 GB RAM and at least a two-core CPU is good enough to execute the code, but for machine learning and deep learning examples, you may have more RAM, perhaps 8 GB or 16 GB, and computational power that uses GPU(s).

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