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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

Basic statistical features for NLP

In the last section, we looked at most of the NLP concepts, tools, and algorithms that can be used to derive features. Now it's time to learn about some statistical features as well. Here, we will explore the statistical aspect. You will learn how statistical concepts help us derive some of the most useful features.

Before we jump into statistical features, as a prerequisite, you need to understand basic mathematical concepts, linear algebra concepts, and probabilistic concepts. So here, we will seek to understand these concepts first and then understand the statistical features.

Basic mathematics

We will begin with the basics of linear algebra and probability; this is because we want...

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