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Deep Learning with R Cookbook

You're reading from   Deep Learning with R Cookbook Over 45 unique recipes to delve into neural network techniques using R 3.5.x

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781789805673
Length 328 pages
Edition 1st Edition
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Authors (3):
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Swarna Gupta Swarna Gupta
Author Profile Icon Swarna Gupta
Swarna Gupta
Rehan Ali Ansari Rehan Ali Ansari
Author Profile Icon Rehan Ali Ansari
Rehan Ali Ansari
Dipayan Sarkar Dipayan Sarkar
Author Profile Icon Dipayan Sarkar
Dipayan Sarkar
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Table of Contents (11) Chapters Close

Preface 1. Understanding Neural Networks and Deep Neural Networks 2. Working with Convolutional Neural Networks FREE CHAPTER 3. Recurrent Neural Networks in Action 4. Implementing Autoencoders with Keras 5. Deep Generative Models 6. Handling Big Data Using Large-Scale Deep Learning 7. Working with Text and Audio for NLP 8. Deep Learning for Computer Vision 9. Implementing Reinforcement Learning 10. Other Books You May Enjoy

Summarizing text using deep learning

With the evolution of the internet, we have been flooded with a lot of voluminous data from various sources such as news articles, social media platforms, blogs, and so on. Text summarization in the field of natural language processing is the technique of creating a concise and accurate summary of textual data, capturing the essential details that are coherent with the source text.

Text summarization can be of two types, which are as follows:

  • Extractive summarization: This method extracts key sentences or phrases from the original source text without modifying them. This approach is simpler.
  • Abstractive summarization: This method, on the other hand, works on a complex mapping between the context of the source text and the summary rather than merely copying words from the input to the output. A significant challenge with this approach is that...
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