Hands-On Generative Adversarial Networks with Keras
This book will explore deep learning and generative models, and their applications in artificial intelligence. You will learn to evaluate and improve your GAN models by eliminating challenges that are encountered in real-world applications. You will implement GAN architectures in various domains such as computer vision, NLP, and audio processing
Offered by
Difficulty Level
Intermediate
Completion Time
9h4m
Language
English
About Book
Who Is This Book For?
This book is for machine learning practitioners, deep learning researchers, and AI enthusiasts who are looking for a mix of theory and hands-on content to implement GANs using Keras. Working knowledge of Python is expected.
Hands-On Generative Adversarial Networks with Keras
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 9h4m total length
Deep Learning Basics and Environment Setup
Introduction to Generative Models
Implementing your fist GAN
Evaluating your first GAN
Improving your first GAN
Synthesizing and Manipulating Images with GANs
Progressive Growing of GANs
Natural Language Generation with GANs
Text-To-Image Synthesis with GANs
Speech Enhancement with GANs
TequilaGAN: Identifying GAN samples
What’s Next in GANs
Related Resources
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