Generative Adversarial Networks with Industrial Use Cases

Free Download Generative Adversarial Networks with Industrial Use Cases: Learning How to Build GAN Applications for Retail, Healthcare, Telecom, Media, Education, and HRTech (English Edition) by Navin K. Manaswi
English | March 5, 2020 | ISBN: 9389423856 | 132 pages | MOBI | 13 Mb
Best Book on GAN

Key FeaturesUnderstanding the deep learning landscape and GAN’s relevanceLearning basics of GANLearning how to build GAN from scratchUnderstanding mathematics and limitations of GANUnderstanding GAN applications for Retail, Healthcare, Telecom, Media and EduTechUnderstanding the important GAN papers such as pix2pixGAN, styleGAN, cycleGAN, DCGANLearning how to build GAN code for industrial applicationsUnderstanding the difference between varieties of GAN
Description
This book aims at simplifying GAN for everyone. This book is very important for machine learning engineers, researchers, students, professors, and professionals. Universities and online course instructors will find this book very interesting for teaching advanced deep learning, specially Generative Adversarial Networks(GAN). Industry professionals, coders, and data scientists can learn GAN from scratch. They can learn how to build GAN codes for industrial applications for Healthcare, Retail, HRTech, EduTech, Telecom, Media, and Entertainment. Mathematics of GAN is discussed and illustrated. KL divergence and other parts of GAN are illustrated and discussed mathematically. This book teaches how to build codes for pix2pix GAN, DCGAN, CGAN, styleGAN, cycleGAN, and many other GAN. Machine Learning and Deep Learning Researchers will learn GAN in the shortest possible time with the help of this book.
What will you learn
Machine Learning Researchers would be comfortable in building advanced deep learning codes for Industrial applicationsData Scientists would start solving very complex problems in deep learningStudents would be ready to join an industry with these skillsAverage data engineers and scientists would be able to develop complex GAN codes to solve the toughest problems in computer vision
Who this book is for
This book is perfect for machine learning engineers, data scientists, data engineers, deep learning professionals and computer vision researchers. This book is also very useful for medical imaging professionals, autonomous vehicles professionals, retail fashion professionals, media & entertainment professional, edutech and HRtech professionals. Professors and Students working in machine learning, deep learning, computer vision and industrial applications would find this book extremely useful.
Table of Contents
1. Basics of GAN
2. GAN Applications
3. Problem with GAN
4. Famous Types Of GANs

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