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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

Understanding the basics of machine learning

First of all, we will understand what machine learning is. Traditionally, programming is all about defining all the steps to reach a certain predefined outcome. During this process of programming, we define each of the minute steps using a programming language that help us achieve our outcome. To give you a basic understanding, I'll take a general example. Suppose that you want to write a program that will help you draw a face. You may first write the code that draws the left eye, then write the code that draws the right eye, then the nose, and so on. Here, you are writing the code for each facial attribute, but ML flips this approach. In ML, we define the outcome and the program learns the steps to achieve the defined output. So, instead of writing code for each facial attribute, we provide hundreds of samples of human faces to...

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