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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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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

Understanding feature engineering

Before jumping into the feature generation techniques, we need to understand feature engineering and its purpose.

What is feature engineering?

Feature engineering is the process of generating or deriving features (attributes or an individual measurable property of a phenomenon) from raw data or corpus that will help us develop NLP applications or solve NLP-related problems.

A feature can be defined as a piece of information or measurable property that is useful when building NLP applications or predicting the output of NLP applications.

We will use ML techniques to process the natural language and develop models that will give us the final output. This model is called the machine learning...

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