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Keras Deep Learning Cookbook

You're reading from   Keras Deep Learning Cookbook Over 30 recipes for implementing deep neural networks in Python

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788621755
Length 252 pages
Edition 1st Edition
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Authors (3):
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Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
Manpreet Singh Ghotra Manpreet Singh Ghotra
Author Profile Icon Manpreet Singh Ghotra
Manpreet Singh Ghotra
Rajdeep Dua Rajdeep Dua
Author Profile Icon Rajdeep Dua
Rajdeep Dua
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Toc

Table of Contents (12) Chapters Close

Preface 1. Keras Installation 2. Working with Keras Datasets and Models FREE CHAPTER 3. Data Preprocessing, Optimization, and Visualization 4. Classification Using Different Keras Layers 5. Implementing Convolutional Neural Networks 6. Generative Adversarial Networks 7. Recurrent Neural Networks 8. Natural Language Processing Using Keras Models 9. Text Summarization Using Keras Models 10. Reinforcement Learning 11. Other Books You May Enjoy

Introduction

Text summarization is a method in natural language processing (NLP) of generating a short and precise summary of a reference document. Producing a summary of a large document manually is a very difficult task. Summarization of a text using machine learning techniques is still an active research topic, and references for further reading are provided at the end of the chapter. Before proceeding to discuss text summarization and how we do it, we should define what a summary is. The summary is a text output that is generated from one or more texts that conveys relevant information from the original text in a shorter form. The goal of automatic text summarization is to transform the source text into a shorter version using semantics. Lately, various approaches have been developed for automated text summarization using NLP techniques, and they have been implemented widely...

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