Generative Adversarial Networks Projects
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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.
Hands On Generative Adversarial Networks With Pytorch 1 X
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Author : John Hany
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-12-12
Hands On Generative Adversarial Networks With Pytorch 1 X written by John Hany 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 2019-12-12 with Computers categories.
Apply deep learning techniques and neural network methodologies to build, train, and optimize generative network models Key FeaturesImplement GAN architectures to generate images, text, audio, 3D models, and moreUnderstand how GANs work and become an active contributor in the open source communityLearn how to generate photo-realistic images based on text descriptionsBook Description With continuously evolving research and development, Generative Adversarial Networks (GANs) are the next big thing in the field of deep learning. This book highlights the key improvements in GANs over generative models and guides in making the best out of GANs with the help of hands-on examples. This book starts by taking you through the core concepts necessary to understand how each component of a GAN model works. You'll build your first GAN model to understand how generator and discriminator networks function. As you advance, you'll delve into a range of examples and datasets to build a variety of GAN networks using PyTorch functionalities and services, and become well-versed with architectures, training strategies, and evaluation methods for image generation, translation, and restoration. You'll even learn how to apply GAN models to solve problems in areas such as computer vision, multimedia, 3D models, and natural language processing (NLP). The book covers how to overcome the challenges faced while building generative models from scratch. Finally, you'll also discover how to train your GAN models to generate adversarial examples to attack other CNN and GAN models. By the end of this book, you will have learned how to build, train, and optimize next-generation GAN models and use them to solve a variety of real-world problems. What you will learnImplement PyTorch's latest features to ensure efficient model designingGet to grips with the working mechanisms of GAN modelsPerform style transfer between unpaired image collections with CycleGANBuild and train 3D-GANs to generate a point cloud of 3D objectsCreate a range of GAN models to perform various image synthesis operationsUse SEGAN to suppress noise and improve the quality of speech audioWho this book is for This GAN book is for machine learning practitioners and deep learning researchers looking to get hands-on guidance in implementing GAN models using PyTorch. You’ll become familiar with state-of-the-art GAN architectures with the help of real-world examples. Working knowledge of Python programming language is necessary to grasp the concepts covered in this book.
Generative Adversarial Networks Project Relevant Overview
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Author : Rodion Kraft
language : en
Publisher:
Release Date : 2022
Generative Adversarial Networks Project Relevant Overview written by Rodion Kraft and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
A Primer On Generative Adversarial Networks
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Author : Sanaa Kaddoura
language : en
Publisher:
Release Date : 2023
A Primer On Generative Adversarial Networks written by Sanaa Kaddoura and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
This book is meant for readers who want to understand GANs without the need for a strong mathematical background. Moreover, it covers the practical applications of GANs, making it an excellent resource for beginners. A Primer on Generative Adversarial Networks is suitable for researchers, developers, students, and anyone who wishes to learn about GANs. It is assumed that the reader has a basic understanding of machine learning and neural networks. The book comes with ready-to-run scripts that readers can use for further research. Python is used as the primary programming language, so readers should be familiar with its basics. The book starts by providing an overview of GAN architecture, explaining the concept of generative models. It then introduces the most straightforward GAN architecture, which explains how GANs work and covers the concepts of generator and discriminator. The book then goes into the more advanced real-world applications of GANs, such as human face generation, deep fake, CycleGANs, and more. By the end of the book, readers will have an essential understanding of GANs and be able to write their own GAN code. They can apply this knowledge to their projects, regardless of whether they are beginners or experienced machine learning practitioners.
Generative Adversarial Networks For Image To Image Translation
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Author : Arun Solanki
language : en
Publisher: Academic Press
Release Date : 2021-06-22
Generative Adversarial Networks For Image To Image Translation written by Arun Solanki and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-22 with Science categories.
Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics in Artificial Intelligence. Generative Adversarial Networks for Image-to-Image Translation provides a comprehensive overview of the GAN (Generative Adversarial Network) concept starting from the original GAN network to various GAN-based systems such as Deep Convolutional GANs (DCGANs), Conditional GANs (cGANs), StackGAN, Wasserstein GANs (WGAN), cyclical GANs, and many more. The book also provides readers with detailed real-world applications and common projects built using the GAN system with respective Python code. A typical GAN system consists of two neural networks, i.e., generator and discriminator. Both of these networks contest with each other, similar to game theory. The generator is responsible for generating quality images that should resemble ground truth, and the discriminator is accountable for identifying whether the generated image is a real image or a fake image generated by the generator. Being one of the unsupervised learning-based architectures, GAN is a preferred method in cases where labeled data is not available. GAN can generate high-quality images, images of human faces developed from several sketches, convert images from one domain to another, enhance images, combine an image with the style of another image, change the appearance of a human face image to show the effects in the progression of aging, generate images from text, and many more applications. GAN is helpful in generating output very close to the output generated by humans in a fraction of second, and it can efficiently produce high-quality music, speech, and images. - Introduces the concept of Generative Adversarial Networks (GAN), including the basics of Generative Modelling, Deep Learning, Autoencoders, and advanced topics in GAN - Demonstrates GANs for a wide variety of applications, including image generation, Big Data and data analytics, cloud computing, digital transformation, E-Commerce, and Artistic Neural Networks - Includes a wide variety of biomedical and scientific applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing, and disease diagnosis - Provides a robust set of methods that will help readers to appropriately and judiciously use the suitable GANs for their applications
The 10th International Conference On Science And Technology Icst
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Author : Ganjar Alfian
language : en
Publisher: Trans Tech Publications Ltd
Release Date : 2025-10-13
The 10th International Conference On Science And Technology Icst written by Ganjar Alfian and has been published by Trans Tech Publications Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-13 with Technology & Engineering categories.
Selected peer-reviewed full text papers from the 10th International Conference on Science and Technology (ICST UGM 2024) Selected peer-reviewed full text papers from the 10th International Conference on Science and Technology (ICST UGM 2024), October 23-24, 2024, Yogyakarta, Indonesia
Machine Learning And Deep Learning Using Python And Tensorflow
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Author : Venkata Reddy Konasani
language : en
Publisher: McGraw Hill Professional
Release Date : 2021-04-29
Machine Learning And Deep Learning Using Python And Tensorflow written by Venkata Reddy Konasani and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Technology & Engineering categories.
Understand the principles and practices of machine learning and deep learning This hands-on guide lays out machine learning and deep learning techniques and technologies in a style that is approachable, using just the basic math required. Written by a pair of experts in the field, Machine Learning and Deep Learning Using Python and TensorFlow contains case studies in several industries, including banking, insurance, e-commerce, retail, and healthcare. The book shows how to utilize machine learning and deep learning functions in today’s smart devices and apps. You will get download links for datasets, code, and sample projects referred to in the text. Coverage includes: Machine learning and deep learning concepts Python programming and statistics fundamentals Regression and logistic regression Decision trees Model selection and cross-validation Cluster analysis Random forests and boosting Artificial neural networks TensorFlow and Keras Deep learning hyperparameters Convolutional neural networks Recurrent neural networks and long short-term memory
Generating A New Reality
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Author : Micheal Lanham
language : en
Publisher:
Release Date : 2021
Generating A New Reality written by Micheal Lanham and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
The emergence of artificial intelligence (AI) has brought us to the precipice of a new age where we struggle to understand what is real, from advanced CGI in movies to even faking the news. AI that was developed to understand our reality is now being used to create its own reality. In this book we look at the many AI techniques capable of generating new realities. We start with the basics of deep learning. Then we move on to autoencoders and generative adversarial networks (GANs). We explore variations of GAN to generate content. The book ends with an in-depth look at the most popular generator projects. By the end of this book you will understand the AI techniques used to generate different forms of content. You will be able to use these techniques for your own amusement or professional career to both impress and educate others around you and give you the ability to transform your own reality into something new. You will: Know the fundamentals of content generation from autoencoders to generative adversarial networks (GANs) Explore variations of GAN Understand the basics of other forms of content generation Use advanced projects such as Faceswap, deepfakes, DeOldify, and StyleGAN2.
Generative Adversarial Networks In Practice
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Author : Mehdi Ghayoumi
language : en
Publisher: CRC Press
Release Date : 2023-12-20
Generative Adversarial Networks In Practice written by Mehdi Ghayoumi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-20 with Computers categories.
This book is an all-inclusive resource that provides a solid foundation on Generative Adversarial Networks (GAN) methodologies, their application to real-world projects, and their underlying mathematical and theoretical concepts. Key Features: Guides you through the complex world of GANs, demystifying their intricacies Accompanies your learning journey with real-world examples and practical applications Navigates the theory behind GANs, presenting it in an accessible and comprehensive way Simplifies the implementation of GANs using popular deep learning platforms Introduces various GAN architectures, giving readers a broad view of their applications Nurture your knowledge of AI with our comprehensive yet accessible content Practice your skills with numerous case studies and coding examples Reviews advanced GANs, such as DCGAN, cGAN, and CycleGAN, with clear explanations and practical examples Adapts to both beginners and experienced practitioners, with content organized to cater to varying levels of familiarity with GANs Connects the dots between GAN theory and practice, providing a well-rounded understanding of the subject Takes you through GAN applications across different data types, highlighting their versatility Inspires the reader to explore beyond this book, fostering an environment conducive to independent learning and research Closes the gap between complex GAN methodologies and their practical implementation, allowing readers to directly apply their knowledge Empowers you with the skills and knowledge needed to confidently use GANs in your projects Prepare to deep dive into the captivating realm of GANs and experience the power of AI like never before with Generative Adversarial Networks (GANs) in Practice. This book brings together the theory and practical aspects of GANs in a cohesive and accessible manner, making it an essential resource for both beginners and experienced practitioners.
Gans In Action
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Author : Aeronis Krynn
language : en
Publisher: Independently Published
Release Date : 2025-09-18
Gans In Action written by Aeronis Krynn and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-18 with categories.
Welcome to GANs in Action: Create Realistic Images & Videos with AI, where we take the mystery out of Generative Adversarial Networks (GANs) and show you just how awesome-and addictive-this AI technology can be. Whether you're an aspiring AI artist, a hobbyist looking to generate realistic images, or someone who just loves the idea of teaching machines to create on their own, this book is your perfect launchpad. We're going to make GANs so approachable that you'll be creating mind-blowing images (and maybe a few quirky ones) before you know it. In this book, we'll guide you step by step through the fascinating world of GANs, from the very first baby steps of setting up your environment to building, training, and fine-tuning your own models. You'll dive deep into how these networks work, explore their unique architecture (the Generator and the Discriminator), and learn why GANs are the powerhouse behind some of the most innovative AI applications today-from realistic image generation to video animation. You'll also get your hands dirty with PyTorch, training models on datasets like MNIST and CelebA, and discover tricks to make sure your GANs are performing at their best. By the time you finish this book, you won't just understand GANs-you'll have built your own! And not only that, but you'll also have the skills to tackle more advanced GAN techniques, explore Conditional GANs (cGANs) for specific image generation, experiment with Deep Convolutional GANs (DCGANs) for high-quality output, and even dive into the world of video and animation. Sounds like a dream, right? But it's all very real, and you're about to bring these creations to life. This book is packed with hands-on projects that will keep you engaged, entertained, and constantly learning. Plus, you'll discover how to evaluate your models, debug training instability, and deploy your creations to the real world. The GAN technology we explore is the future of creativity, and by the end of this journey, you'll be ready to harness it for everything from AI-powered art to deepfake technology. Who knows, maybe the next viral meme will be something you've generated. But don't stop here! This book is just one part of The Generative AI Blueprint series. If you found the magic of GANs exciting, you're going to love the other books in the series. Start with Generative AI for Beginners if you need a gentle introduction, or dive deeper into technical aspects with Python for AI and Deep Learning Essentials. If you're craving more hands-on projects, Autoencoders & VAEs: Hands-On Generative AI Projects will be your next stop, and you can even explore the world of AI art with Stable Diffusion & AI Art: Generate Stunning Images with AI. Trust me, there's no shortage of fun, and this series will keep you on your toes as you master the many aspects of Generative AI. So, what are you waiting for? Grab this book, fire up your Python environment, and let's get creating. The world of GANs is full of possibilities, and you're about to unlock a whole new realm of AI-powered creativity. Let's do this!