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Gans in Action: Deep Learning with Generative Adversarial Networks

Gans in Action: Deep Learning with Generative Adversarial Networks 0.0分

资源最后更新于 2020-08-23 08:24:18

作者:Jakub Langr

出版社:Manning Publications

出版日期:2019-01

ISBN:9781617295560

文件格式: pdf

标签: GAN 深度学习 AI 计算机科学 计算机 DeepLearning 机器学习

简介· · · · · ·

Summary

GANs in Action teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning. In this book, you'll learn how to start building your own simple adversarial system as you explore the foundation of GAN architecture: the generator and discriminator networks.

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目录

Table of Contents
PART 1 - INTRODUCTION TO GANS AND GENERATIVE MODELING
Introduction to GANs
Intro to generative modeling with autoencoders
Your first GAN: Generating handwritten digits
Deep Convolutional GAN
PART 2 - ADVANCED TOPICS IN GANS
Training and common challenges: GANing for success
Progressing with GANs
Semi-Supervised GAN
Conditional GAN
CycleGAN
PART 3 - WHERE TO GO FROM HERE
Adversarial examples
Practical applications of GANs
Looking ahead