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Neural Network Programming with TensorFlow

You're reading from  Neural Network Programming with TensorFlow

Product type Book
Published in Nov 2017
Publisher Packt
ISBN-13 9781788390392
Pages 274 pages
Edition 1st Edition
Languages
Authors (2):
Manpreet Singh Ghotra Manpreet Singh Ghotra
Profile icon Manpreet Singh Ghotra
Rajdeep Dua Rajdeep Dua
Profile icon Rajdeep Dua
View More author details
Toc

Table of Contents (17) Chapters close

Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Maths for Neural Networks 2. Deep Feedforward Networks 3. Optimization for Neural Networks 4. Convolutional Neural Networks 5. Recurrent Neural Networks 6. Generative Models 7. Deep Belief Networking 8. Autoencoders 9. Research in Neural Networks 10. Getting started with TensorFlow

Summary


Generative models are a fast advancing area of study and research. As we proceed to advance these models and grow the training and datasets, we can expect to generate data examples that depict completely believable images, finally. This can be used in several applications such as image denoising, painting, structured prediction, and exploration in reinforcement learning.

The deeper promise of this effort is that, in the process of building generative models, we will enrich the computer with an understanding of the world and what elements it is made up of.

 

 

 

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