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Python Natural Language Processing

You're reading from Python Natural Language Processing

Product type Book

Published in Jul 2017

Publisher Packt

ISBN-13 9781787121423

Pages 486 pages

Edition 1st Edition

Languages

Concepts

Artificial Intelligence

Table of Contents (13) Chapters

Preface

1. Introduction

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 NLU

This section is coding-based and I will explain concepts as we go. The application that we are building here is one of the main applications in NLU.

There are so many languages spoken, written, or read by humans. Have you ever tried to learn a new language? If yes, then you know how difficult it is to acquire the skill of speaking a new language or writing a new language. Have you ever thought how Google translator is used in order to translate languages? If you are curious, then let's begin developing a machine translation application using a deep learning technique. Don't worry about questions like what type of DNN we will use because I'm explaining things to you in detail. So let's do some translation!

Note that DL takes a lot of computing power so we are not going to actually train the model, although I will give you details...

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