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Deep Learning with PyTorch

You're reading from   Deep Learning with PyTorch A practical approach to building neural network models using PyTorch

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788624336
Length 262 pages
Edition 1st Edition
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Author (1):
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Vishnu Subramanian Vishnu Subramanian
Author Profile Icon Vishnu Subramanian
Vishnu Subramanian
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Table of Contents (11) Chapters Close

Preface 1. Getting Started with Deep Learning Using PyTorch 2. Building Blocks of Neural Networks FREE CHAPTER 3. Diving Deep into Neural Networks 4. Fundamentals of Machine Learning 5. Deep Learning for Computer Vision 6. Deep Learning with Sequence Data and Text 7. Generative Networks 8. Modern Network Architectures 9. What Next? 10. Other Books You May Enjoy

Neural style transfer

We humans generate artwork with different levels of accuracy and complexity. Though the process of creating art could be a very complex process, it can be seen as a combination of the two most important factors, namely, what to draw and how to draw. What to draw is inspired by what we see around us, and how we draw will also take influences from certain things that are found around us. This could be an oversimplification from an artist's perspective, but for understanding how we can create artwork using deep learning algorithms, it is very useful. We will train a deep learning algorithm to take content from one image and then draw it according to a specific artistic style. If you are an artist or in the creative industry, you can directly use the amazing research that has gone on in recent years to improve this and create something cool within the domain...

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