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Neural Networks with Keras Cookbook

You're reading from   Neural Networks with Keras Cookbook Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789346640
Length 568 pages
Edition 1st Edition
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Authors (2):
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V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Srinivas Pradeep Srinivas Pradeep
Author Profile Icon Srinivas Pradeep
Srinivas Pradeep
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Toc

Table of Contents (18) Chapters Close

Preface 1. Building a Feedforward Neural Network 2. Building a Deep Feedforward Neural Network FREE CHAPTER 3. Applications of Deep Feedforward Neural Networks 4. Building a Deep Convolutional Neural Network 5. Transfer Learning 6. Detecting and Localizing Objects in Images 7. Image Analysis Applications in Self-Driving Cars 8. Image Generation 9. Encoding Inputs 10. Text Analysis Using Word Vectors 11. Building a Recurrent Neural Network 12. Applications of a Many-to-One Architecture RNN 13. Sequence-to-Sequence Learning 14. End-to-End Learning 15. Audio Analysis 16. Reinforcement Learning 17. Other Books You May Enjoy

Building word vectors using GloVe

Similar to the way word2vec generates word vectors, GloVe (short for Global Vectors for Word Representation), also generates word vectors but using a different method. In this section, we will explore how GloVe works and then get into the implementation details of GloVe.

Getting ready

GloVe aims to achieve two goals:

  • Creating word vectors that capture meaning in vector space
  • Taking advantage of global count statistics instead of only local information

GloVe learns word vectors by looking at the cooccurrence matrix of words and optimizing for a loss function. The working details of the GloVe algorithm can be understood from the following example:

Let's consider a scenario where there...

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