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Generative Adversarial Networks Cookbook

You're reading from  Generative Adversarial Networks Cookbook

Product type Book
Published in Dec 2018
Publisher Packt
ISBN-13 9781789139907
Pages 268 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Josh Kalin Josh Kalin
Profile icon Josh Kalin
LinkedIn
Josh Kalin is a Physicist and Technologist focused on the intersection of robotics and machine learning. Josh works on advanced sensors, industrial robotics, machine learning, and automated vehicle research projects. Josh holds degrees in Physics, Mechanical Engineering, and Computer Science. In his free time, he enjoys working on cars (has owned 36 vehicles and counting), building computers, and learning new techniques in robotics and machine learning (like writing this book).
See other products by Josh Kalin

Table of Contents (17) Chapters

Title Page
Copyright and Credits
About Packt
Dedication
Contributors
Preface
Dedication2
1. What Is a Generative Adversarial Network? 2. Data First, Easy Environment, and Data Prep 3. My First GAN in Under 100 Lines 4. Dreaming of New Outdoor Structures Using DCGAN 5. Pix2Pix Image-to-Image Translation 6. Style Transfering Your Image Using CycleGAN 7. Using Simulated Images To Create Photo-Realistic Eyeballs with SimGAN 8. From Image to 3D Models Using GANs 1. Other Books You May Enjoy Index

But first, set up your development environment

What's a development environment? Everyone thinks setting up a development environment needs to be this incredibly arduous process. The installation process could be worse. It's actually quite simple and I intend to show you the basics in this recipe.

Getting ready

Let's lay out the requirements for the equipment you'll need to be successful in this book:

  • GPU: 10 series CUDA-enabled Nidea GPU 
  • Operating system: Ubuntu Linux 16.04+
  • CPU/RAM: i5 or i7 with at least 8 GB of RAM

First and foremost, the GPU is a requirement for this type of book. Although these algorithms can technically train on a CPU, it could take days in some cases for a single model to converge. It can take a GPU a day or more to converge in some instances. GPUs offer an immense computational power increase over CPUs and hence are a necessity to ensure that you get the most out of this book. It's easy today to find a laptop with a 1,060 or better in it for around $900. 

Ubuntu is the...

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Authors (1)

Profile icon Josh Kalin
LinkedIn
Josh Kalin is a Physicist and Technologist focused on the intersection of robotics and machine learning. Josh works on advanced sensors, industrial robotics, machine learning, and automated vehicle research projects. Josh holds degrees in Physics, Mechanical Engineering, and Computer Science. In his free time, he enjoys working on cars (has owned 36 vehicles and counting), building computers, and learning new techniques in robotics and machine learning (like writing this book).
See other products by Josh Kalin

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