Generative Adversarial Networks Projects
In this book, we will use different complexities of datasets in order to build end-to-end projects. With every chapter, the level of complexity and operations will become advanced. It consists of 8 full-fledged projects covering approaches such as 3D-GAN, Age-cGAN, DCGAN, SRGAN, StackGAN, and CycleGAN with real-world use cases.
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Difficulty Level
Intermediate
Completion Time
10h32m
Language
English
About Book
Who Is This Book For?
If you’re a data scientist, machine learning 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.
Generative Adversarial Networks Projects
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 10h32m total length
Introduction to Generative Adversarial Networks
3D-GAN - Generating Shapes Using GANs
Face Aging Using Conditional GAN
Generating Anime Characters Using DCGANs
Using SRGANs to Generate Photo-Realistic Images
StackGAN- Text to Photo-Realistic Image Synthesis
CycleGAN- Turn Paintings into Photos
Conditional GAN - Image-to-Image Translation Using Conditional Adversarial Networks
Predicting the Future of GANs
Related Resources
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