The Gan Book
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The Gan Book
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Author : Kartik Chaudhary
language : en
Publisher: Kartik Chaudhary (Drops of AI)
Release Date :
The Gan Book written by Kartik Chaudhary and has been published by Kartik Chaudhary (Drops of AI) this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Key Features - Learn generative learning approach of ML and its key differences from the discriminative learning approach. - Understand why GANs are difficult to train, and key techniques to make their training stable to get impressive results. - Implement multiple variants of GANs for solving problems such as image generation, image-to-image translation, image super- resolution and so on. Book Description Generative Adversarial Networks have become quite popular due to their wide variety of applications in the fields of Computer Vision, Digital Marketing, Creative artwork and so on. One key challenge with GANs is that they are very difficult to train. This book is a comprehensive guide that highlights the common challenges of training GANs and also provides guidelines for developing GANs in such a way that they result in stable training and high-quality results. This book also explains the generative learning approach of training ML models and its key differences from the discriminative learning approach. After covering the different generative learning approaches, this book deeps dive more into the Generative Adversarial Network and their key variants. This book takes a hands-on approach and implements multiple generative models such as Pixel CNN, VAE, GAN, DCGAN, CGAN, SGAN, InfoGAN, ACGAN, WGAN, LSGAN, WGAN-GP, Pix2Pix, CycleGAN, SRGAN, DiscoGAN, CartoonGAN, Context Encoder and so on. It also provides a detailed explanation of some advanced GAN variants such as BigGAN, PGGAN, StyleGAN and so on. This book will make you a GAN champion in no time. What will you learn - Learn about the generative learning approach of training ML models - Understand key differences of the generative learning approach from the discriminative learning approach - Learn about various generative learning approaches and key technical aspects behind them - Understand and implement the Generative Adversarial Networks in details - Learn about some key challenges faced during GAN training and two common training failure modes - Build expertise in the best practices and guidelines for developing and training stable GANs - Implement multiple variants of GANs and verify their results on your own datasets - Learn about the adversarial examples, some key applications of GANs and common evaluation strategies Who this book is for If you are a ML practitioner who wants to learn about generative learning approaches and get expertise in Generative Adversarial Networks for generating high-quality and realistic content, this book is for you. Starting from a gentle introduction to the generative learning approaches, this book takes you through different variants of GANs, explaining some key technical and intuitive aspects about them. This book provides hands-on examples of multiple GAN variants and also, explains different ways to evaluate them. It covers key applications of GANs and also, explains the adversarial examples. Table of Contents 1. Generative Learning 2. Generative Adversarial Networks 3. GAN Failure Modes 4. Deep Convolutional GANs 4(II). Into the Latent Space 5. Towards stable GANs 6. Conditional GANs 7. Better Loss functions 8. Image-to-Image Translation 9. Other GANs and experiments 9(II). Advanced Scaling of GANs 10. How to evaluate GANs? 11. Adversarial Examples 12. Impressive Applications of GANs 13. Top Research Papers
Generative Adversarial Networks Cookbook
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Author : Josh Kalin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-31
Generative Adversarial Networks Cookbook written by Josh Kalin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-31 with Computers categories.
Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and Keras Key FeaturesUnderstand the common architecture of different types of GANsTrain, optimize, and deploy GAN applications using TensorFlow and KerasBuild generative models with real-world data sets, including 2D and 3D dataBook Description Developing Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand. This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use. By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away. What you will learnStructure a GAN architecture in pseudocodeUnderstand the common architecture for each of the GAN models you will buildImplement different GAN architectures in TensorFlow and KerasUse different datasets to enable neural network functionality in GAN modelsCombine different GAN models and learn how to fine-tune themProduce a model that can take 2D images and produce 3D modelsDevelop a GAN to do style transfer with Pix2PixWho this book is 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.
Joined
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Author : Mara Gan
language : en
Publisher:
Release Date : 2018-03-27
Joined written by Mara Gan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-27 with categories.
Duty and prophecy get in the way of everything.All I ever wanted to do was read my books, play my sports, and help people. Life and prophecy had other things in mind.Helping people is what I do; as an empath and semi-frequent telepath, I can easily sense and understand people's needs and emotions. Sometimes even before they do. Being able to read everyone¿s thoughts and feelings all the time can drive me crazy with anxiety, but that moment when I can finally make someone¿s life better makes everything worth it.Unfortunately, I¿m also the next in line to rule the galaxy, I¿m the only diplomat most planets will listen to, assassins try to kill me on an annoyingly regular basis, and a much-vaunted Prophecy has decreed that I¿m going to die. Oh, and someone blew up my home planet.Kind of a lot to deal with, right?Too bad I just got another problem: a big, irritating, overbearing bodyguard with serious anger management issues. And I think I¿m falling for him.
Hands On Generative Adversarial Networks With Keras
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Author : Rafael Valle
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-03
Hands On Generative Adversarial Networks With Keras written by Rafael Valle and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-03 with Mathematics categories.
Develop generative models for a variety of real-world use-cases and deploy them to production Key FeaturesDiscover various GAN architectures using Python and Keras libraryUnderstand how GAN models function with the help of theoretical and practical examplesApply your learnings to become an active contributor to open source GAN applicationsBook Description Generative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning. This book will be your first step towards understanding GAN architectures and tackling the challenges involved in training them. This book opens with an introduction to deep learning and generative models, and their applications in artificial intelligence (AI). You will then learn how to build, evaluate, and improve your first GAN with the help of easy-to-follow examples. The next few chapters will guide you through training a GAN model to produce and improve high-resolution images. You will also learn how to implement conditional GANs that give you the ability to control characteristics of GAN outputs. You will build on your knowledge further by exploring a new training methodology for progressive growing of GANs. Moving on, you'll gain insights into state-of-the-art models in image synthesis, speech enhancement, and natural language generation using GANs. In addition to this, you'll be able to identify GAN samples with TequilaGAN. By the end of this book, you will be well-versed with the latest advancements in the GAN framework using various examples and datasets, and you will have the skills you need to implement GAN architectures for several tasks and domains, including computer vision, natural language processing (NLP), and audio processing. Foreword by Ting-Chun Wang, Senior Research Scientist, NVIDIA What you will learnLearn how GANs work and the advantages and challenges of working with themControl the output of GANs with the help of conditional GANs, using embedding and space manipulationApply GANs to computer vision, NLP, and audio processingUnderstand how to implement progressive growing of GANsUse GANs for image synthesis and speech enhancementExplore the future of GANs in visual and sonic artsImplement pix2pixHD to turn semantic label maps into photorealistic imagesWho this book is for This book is for machine learning practitioners, deep learning researchers, and AI enthusiasts who are looking for a perfect mix of theory and hands-on content in order to implement GANs using Keras. Working knowledge of Python is expected.
Generative Adversarial Networks Projects
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Author : Kailash Ahirwar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-01-31
Generative Adversarial Networks Projects written by Kailash Ahirwar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-31 with Mathematics categories.
Explore various Generative Adversarial Network architectures using the Python ecosystem Key FeaturesUse different datasets to build advanced projects in the Generative Adversarial Network domainImplement projects ranging from generating 3D shapes to a face aging applicationExplore the power of GANs to contribute in open source research and projectsBook Description Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for training neural networks as you build seven end-to-end projects in the GAN domain. Generative Adversarial Network Projects begins by covering the concepts, tools, and libraries that you will use to build efficient projects. You will also use a variety of datasets for the different projects covered in the book. The level of complexity of the operations required increases with every chapter, helping you get to grips with using GANs. You will cover popular approaches such as 3D-GAN, DCGAN, StackGAN, and CycleGAN, and you’ll gain an understanding of the architecture and functioning of generative models through their practical implementation. By the end of this book, you will be ready to build, train, and optimize your own end-to-end GAN models at work or in your own projects. What you will learnTrain a network on the 3D ShapeNet dataset to generate realistic shapesGenerate anime characters using the Keras implementation of DCGANImplement an SRGAN network to generate high-resolution imagesTrain Age-cGAN on Wiki-Cropped images to improve face verificationUse Conditional GANs for image-to-image translationUnderstand the generator and discriminator implementations of StackGAN in KerasWho this book is 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.
Dragon
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Author : Rose Gan Rose Gan
language : en
Publisher: Monsoon Books
Release Date : 2021-11-01
Dragon written by Rose Gan Rose Gan and has been published by Monsoon Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-01 with Fiction categories.
Before Raffles, before Rajah Brooke, there was Francis Light, the 18th-century trailblazer in the Malay Archipelago. The 18th-century Straits of Malacca is in crisis, beleaguered by the Dutch, the Bugis, and the clash between Siam and Burma. Enter Francis Light, devious manipulator of the status quo, joined by a cast of real historical figures from the courts of Siam and Kedah and from the East India Company, including Sultan Muhammed Jiwa, King Tak Sin, Warren Hastings and Martinha Rozells, a young Eurasian woman of noble birth. From humble origins in Suffolk, England, Light struggles against the social prejudices of his day. His subsequent adventures as a naval officer and country ship captain take him from India to Sumatra, the Straits of Malacca to Siam, through shipwreck, sea battles, pirate raids and tropical disease. But Light’s most difficult challenge is his ultimate dream: to establish a British port in the Indies on behalf of the East India Company. Dragon, the first volume of Penang Chronicles, charts Francis Light’s colourful adventures in the decades before the settlement of Penang island, the Honourable Company’s first possession on the Malay Peninsula.
Generative Adversarial Networks With Industrial Use Cases
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Author : Navin K Manaswi
language : en
Publisher: BPB Publications
Release Date : 2020-03-04
Generative Adversarial Networks With Industrial Use Cases written by Navin K Manaswi and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-04 with Computers categories.
Best Book on GAN Ê DESCRIPTIONÊ 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. Ê KEY FEATURESÊÊ - Understanding the deep learning landscape and GANÕs relevance - Learning basics of GAN - Learning how to build GAN from scratch - Understanding mathematics and limitations of GAN - Understanding GAN applications for Retail, Healthcare, Telecom, Media and EduTech - Understanding the important GAN papers such as pix2pixGAN, styleGAN, cycleGAN, DCGAN - Learning how to build GAN code for industrial applications - Understanding the difference between varieties of GAN WHAT WILL YOU LEARNÊ _ÊMachine Learning Researchers would be comfortable in building advanced deep learning codes for Industrial applications _ÊData Scientists would start solving very complex problems in deep learning _ÊStudents would be ready to join an industry with these skills _ÊAverage data engineers and scientists would be able to develop complex GAN codes to solve the toughest problems in computer vision Ê WHO THIS BOOK IS FORÊÊ 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 professionals, 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. Introduction 3. Problem with GANÊ 4. Famous Types Of GANs
Gans In Action
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Author : Jakub Langr
language : en
Publisher: Manning
Release Date : 2019-10-07
Gans In Action written by Jakub Langr and has been published by Manning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-07 with Computers categories.
Deep learning systems have gotten really great at identifying patterns in text, images, and video. But applications that create realistic images, natural sentences and paragraphs, or native-quality translations have proven elusive. Generative Adversarial Networks, or GANs, offer a promising solution to these challenges by pairing two competing neural networks' one that generates content and the other that rejects samples that are of poor quality. GANs in Action: Deep learning with Generative Adversarial Networks teaches you how to build and train your own generative adversarial networks. First, you'll get an introduction to generative modelling and how GANs work, along with an overview of their potential uses. Then, you'll start building your own simple adversarial system, as you explore the foundation of GAN architecture: the generator and discriminator networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Hands On Generative Adversarial Networks With Keras
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Author : Rafael Valle
language : en
Publisher:
Release Date : 2019
Hands On Generative Adversarial Networks With Keras written by Rafael Valle and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Develop generative models for a variety of real-world use cases and deploy them to production Key Features Discover various GAN architectures using a Python and Keras library Understand how GAN models function with the help of theoretical and practical examples Apply your learnings to become an active contributor to open source GAN applications Book Description Generative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning. This book will be your first step toward understanding GAN architectures and tackling the challenges involved in training them. This book opens with an introduction to deep learning and generative models and their applications in artificial intelligence (AI). You will then learn how to build, evaluate, and improve your first GAN with the help of easy-to-follow examples. The next few chapters will guide you through training a GAN model to produce and improve high-resolution images. You will also learn how to implement conditional GANs that enable you to control characteristics of GAN output. You will build on your knowledge further by exploring a new training methodology for progressive growing of GANs. Moving on, you'll gain insights into state-of-the-art models in image synthesis, speech enhancement, and natural language generation using GANs. In addition to this, you'll be able to identify GAN samples with TequilaGAN. By the end of this book, you will be well-versed with the latest advancements in the GAN framework using various examples and datasets, and you will have developed the skills you need to implement GAN architectures for several tasks and domains, including computer vision, natural language processing (NLP), and audio processing. Foreword by Ting-Chun Wang, Senior Research Scientist, NVIDIA What you will learn Discover how GANs work and the advantages and challenges of working with them Control the output of GANs with the help of conditional GANs, using embedding and space manipulation Apply GANs to computer vision, natural language processing (NLP), and audio processing Understand how to implement progressive growing of GANs Use GANs for image synthesis and speech enhancement Explore the future of GANs in visual and sonic arts Implement pix2pixHD to turn semantic label maps into photorealistic images Who this book is 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 co ...
Handbook Of Gan Semiconductor Materials And Devices
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Author : Wengang (Wayne) Bi
language : en
Publisher: CRC Press
Release Date : 2017-10-20
Handbook Of Gan Semiconductor Materials And Devices written by Wengang (Wayne) Bi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-20 with Science categories.
This book addresses material growth, device fabrication, device application, and commercialization of energy-efficient white light-emitting diodes (LEDs), laser diodes, and power electronics devices. It begins with an overview on basics of semiconductor materials, physics, growth and characterization techniques, followed by detailed discussion of advantages, drawbacks, design issues, processing, applications, and key challenges for state of the art GaN-based devices. It includes state of the art material synthesis techniques with an overview on growth technologies for emerging bulk or free standing GaN and AlN substrates and their applications in electronics, detection, sensing, optoelectronics and photonics. Wengang (Wayne) Bi is Distinguished Chair Professor and Associate Dean in the College of Information and Electrical Engineering at Hebei University of Technology in Tianjin, China. Hao-chung (Henry) Kuo is Distinguished Professor and Associate Director of the Photonics Center at National Chiao-Tung University, Hsin-Tsu, Taiwan, China. Pei-Cheng Ku is an associate professor in the Department of Electrical Engineering & Computer Science at the University of Michigan, Ann Arbor, USA. Bo Shen is the Cheung Kong Professor at Peking University in China.