Generative Adversarial Networks Cookbook
Generative Adversarial Networks have opened up many new possibilities in the machine learning domain. This book is all you need to implement different types of GANs using TensorFlow and Keras, in order to provide optimized and efficient deep learning solutions.
Offered by
Difficulty Level
Intermediate
Completion Time
8h56m
Language
English
About Book
Who Is This Book For?
This book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.
Generative Adversarial Networks Cookbook
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 8h56m total length
What is a Generative Adversarial Network?
Data First - How to prepare your dataset
My First GAN in under 100 lines
Dreaming new Kitchens using DCGAN
Pix2Pix Image-to-Image Translation
Style Transfering Your image using CycleGAN
Use Simulated Images to Create Photo Realistic Eyeballs using simGAN
From Image to 3D Models using GANs
Related Resources
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