{"product_id":"hands-on-generative-adversarial-networks-with-keras-pstrong-your-guide-to-implementing-next-generation-generative-adversarial-networks-p","title":"Hands-On Generative Adversarial Networks with Keras","description":"\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\u003cb\u003eDevelop generative models for a variety of real-world use-cases and deploy them to production\u003c\/b\u003e\u003c\/p\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eKey Features\u003c\/strong\u003e\u003c\/h4\u003e\u003cul style=\"margin: 0px 0px 18px 20px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eDiscover various GAN architectures using Python and Keras library\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eUnderstand how GAN models function with the help of theoretical and practical examples\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eApply your learnings to become an active contributor to open source GAN applications\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eBook Description\u003c\/strong\u003e\u003c\/h4\u003e\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eGenerative 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.\u003c\/p\u003e\u003cp style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eThis 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.\u003c\/p\u003e\u003cp style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eBy 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.\u003c\/p\u003e\u003cp style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eForeword by Ting-Chun Wang, Senior Research Scientist, NVIDIA\u003c\/p\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eWhat you will learn\u003c\/strong\u003e\u003c\/h4\u003e\u003cul style=\"margin: 0px 0px 18px 20px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eLearn how GANs work and the advantages and challenges of working with them\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eControl the output of GANs with the help of conditional GANs, using embedding and space manipulation\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eApply GANs to computer vision, NLP, and audio processing\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eUnderstand how to implement progressive growing of GANs\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eUse GANs for image synthesis and speech enhancement\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eExplore the future of GANs in visual and sonic arts\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eImplement pix2pixHD to turn semantic label maps into photorealistic images\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eWho this book is for\u003c\/strong\u003e\u003c\/h4\u003e\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eThis 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.\u003c\/p\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eTable of Contents\u003c\/strong\u003e\u003c\/h4\u003e\u003col style=\"color: rgb(136, 136, 136); margin-top: 0px; margin-right: 0px; margin-left: 22px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\" margin-bottom:=\"\"\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eDeep Learning Basics and Environment Setup\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eIntroduction to Generative Models\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eImplementing your fist GAN\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eEvaluating your first GAN\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eImproving your first GAN\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eSynthesizing and Manipulating Images with GANs\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eProgressive Growing of GANs\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eNatural Language Generation with GANs\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eText-To-Image Synthesis with GANs\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eSpeech Enhancement with GANs\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eTequilaGAN: Identifying GAN samples\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eWhat's Next in GANs\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ol\u003e","brand":"Packt Publishing","offers":[{"title":"Default Title","offer_id":50506200154182,"sku":"9781789538205","price":2475.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/smaller_ez2t-c3.png?v=1790322848","url":"https:\/\/cb-india.com\/products\/hands-on-generative-adversarial-networks-with-keras-pstrong-your-guide-to-implementing-next-generation-generative-adversarial-networks-p","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}