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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
Toc

Table of Contents (13) Chapters close

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 and deep neural networks

Now, just shift from ANN to DNN. In the upcoming section, we will see deep learning, architecture of DNN, and compare the approaches of DL for NLP and ML for NLP.

Revisiting DL

We have seen some basic details about DL. Here, the purpose is just to recall things as a little refresher. ANN that is not two or three layers but many layers deep is called DNN. When we use many layers deep neural networks on lots of data using lots of computing power, we call this process deep learning.

Let's see the architecture of a deep neural network.

The basic architecture of DNN

...
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