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Generative Adversarial Networks Projects

You're reading from Generative Adversarial Networks Projects Build next-generation generative models using TensorFlow and Keras

Product type Paperback

Published in Jan 2019

Publisher Packt

ISBN-13 9781789136678

Length 316 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Author (1):

Kailash Ahirwar

View More author details

Table of Contents (11) Chapters

Preface

1. Introduction to Generative Adversarial Networks

2. 3D-GAN - Generating Shapes Using GANs FREE CHAPTER

3. Face Aging Using Conditional GAN

4. Generating Anime Characters Using DCGANs

5. Using SRGANs to Generate Photo-Realistic Images

6. StackGAN - Text to Photo-Realistic Image Synthesis

7. CycleGAN - Turn Paintings into Photos

8. Conditional GAN - Image-to-Image Translation Using Conditional Adversarial Networks

9. Predicting the Future of GANs

10. Other Books You May Enjoy

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Who this book is for

If you're a data scientist, ML developer, deep learning practitioner, or AI enthusiast looking for a project guide to test your knowledge and expertise in building real-world GANs models, this book is for you.

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Authors (1)

Ahirwar

Ahirwar

Kailash Ahirwar is a machine learning and deep learning enthusiast. He has worked in many areas of Artificial Intelligence (AI), ranging from natural language processing and computer vision to generative modeling using GANs. He is a co-founder and CTO of Mate Labs. He uses GANs to build different models, such as turning paintings into photos and controlling deep image synthesis with texture patches. He is super optimistic about AGI and believes that AI is going to be the workhorse of human evolution.

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