{"product_id":"138268","title":"Generative AI that learns while creating ","description":"\u003ccenter\u003e\u003cdiv style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/tmgdisk01.cafe24.com\/images\/vs\/4172\/sv\/3jXPCfMPLzDqiYwn0SVXnwLV6f2pSz.png?v=1765061730\" style=\"max-width:100%;max-height:10px\"\u003e\u003c\/div\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\n\n\u003cdiv style=\"width:95%\"\u003e\n\n \u003cdiv style=\"text-align:center;font-size:30px;font-weight:bolder;line-height:1.6em\"\u003eGenerative AI that learns while creating \u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"border-bottom:1px;border-bottom-style:dotted;border-color:;padding-bottom:20px\"\u003e\u003ccenter\u003e\u003ctable align=\"center\" width=\"100%\"\u003e\u003ctbody style=\"border:0px\"\u003e\n\n\u003ctr\u003e\u003ctd align=\"center\" style=\"line-height:1.2em;text-align:center;font-size:18px;color:black;font-weight:bold;padding-bottom:20px;\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\u003ctr\u003e\u003ctd style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/image.yes24.com\/goods\/122338458\/XL\" style=\"max-width:100%;height:auto\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\u003c\/table\u003e\u003c\/center\u003e\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;{split_style6}padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e Description \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;word-break:break-all;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eBook Introduction\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e\u003cdiv\u003e \u003cb\u003eA Complete Guide to Generative AI: Transcending the Boundaries of Evolution and Innovation\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e This book explains everything from the basics of deep learning to the latest generative AI models.\u003cbr\u003e We'll cover how to use TensorFlow and Keras to build impressive generative deep learning models, including variational autoencoders (VAEs), generative adversarial networks (GANs), transformers, normalized flow models, energy-based models, and denoising diffusion models.\u003cbr\u003e Learn how to use various generative AI to efficiently train models and create creative generative models.\u003cbr\u003e\n\u003c\/div\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cul\u003e\u003cli\u003e You can preview some of the book's contents.\u003cbr\u003e \u003cspan\u003ePreview\u003c\/span\u003e\n\n\u003c\/li\u003e\u003c\/ul\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eindex\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e \u003cb\u003e[PART 1: Introduction to Generative Deep Learning]\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e CHAPTER 1 Generative Modeling\u003cbr\u003e _1.1 What is generative modeling?\u003cbr\u003e _1.2 First generation model\u003cbr\u003e _1.3 Core probability theory\u003cbr\u003e _1.4 Generative Model Classification\u003cbr\u003e _1.5 Generating Deep Learning Example Code\u003cbr\u003e _1.6 Summary\u003cbr\u003e\u003cbr\u003e CHAPTER 2 DEEP LEARNING\u003cbr\u003e _2.1 Data for deep learning \u003cbr\u003e_2.2 Deep Neural Networks\u003cbr\u003e _2.3 Multilayer Perceptron\u003cbr\u003e _2.4 Convolutional Neural Network\u003cbr\u003e _2.5 Summary\u003cbr\u003e\u003cbr\u003e \u003cb\u003e[PART 2: 6 Generative Modeling Methods]\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e CHAPTER 3 Variational Autoencoders\u003cbr\u003e _3.1 Introduction\u003cbr\u003e _3.2 Autoencoder\u003cbr\u003e _3.3 Variational Autoencoder\u003cbr\u003e _3.4 Exploring the latent space\u003cbr\u003e _3.5 Summary\u003cbr\u003e\u003cbr\u003e CHAPTER 4 Generative Adversarial Networks\u003cbr\u003e _4.1 Introduction\u003cbr\u003e _4.2 Deep Convolutional GAN ​​(DCGAN)\u003cbr\u003e _4.3 Wasserstein GAN-Gradient Penalty (WGAN-GP)\u003cbr\u003e _4.4 Conditional GAN ​​(CGAN)\u003cbr\u003e _4.5 Summary\u003cbr\u003e\u003cbr\u003e CHAPTER 5 Autoregressive Models\u003cbr\u003e _5.1 Introduction\u003cbr\u003e _5.2 Introduction to LSTM Networks\u003cbr\u003e _5.3 RNN Extension\u003cbr\u003e _5.4 PixelCNN\u003cbr\u003e _5.5 Summary\u003cbr\u003e\u003cbr\u003e CHAPTER 6: NORMALIZING FLOW MODEL\u003cbr\u003e _6.1 Introduction\u003cbr\u003e _6.2 Normalizing Flow\u003cbr\u003e _6.3 RealNVP\u003cbr\u003e _6.4 Other normalizing flow models\u003cbr\u003e _6.5 Summary\u003cbr\u003e\u003cbr\u003e CHAPTER 7 Energy-Based Models\u003cbr\u003e _7.1 Introduction\u003cbr\u003e _7.2 Energy-based model\u003cbr\u003e _7.3 Summary\u003cbr\u003e\u003cbr\u003e CHAPTER 8 Diffusion Models\u003cbr\u003e _8.1 Introduction\u003cbr\u003e _8.2 Noise Reduction Diffusion Model\u003cbr\u003e _8.3 Summary\u003cbr\u003e\u003cbr\u003e \u003cb\u003e[PART 3 Applications of Generative Modeling]\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e CHAPTER 9 TRANSFORMERS\u003cbr\u003e _9.1 Introduction\u003cbr\u003e _9.2 GPT\u003cbr\u003e _9.3 Other Transformers\u003cbr\u003e _9.4 Summary\u003cbr\u003e\u003cbr\u003e CHAPTER 10 ADVANCED GAN\u003cbr\u003e _10.1 Introduction \u003cbr\u003e_10.2 ProGAN\u003cbr\u003e _10.3 StyleGAN\u003cbr\u003e _10.4 StyleGAN2\u003cbr\u003e _10.5 Other important GANs\u003cbr\u003e _10.6 Summary\u003cbr\u003e\u003cbr\u003e CHAPTER 11 MUSIC CREATION\u003cbr\u003e _11.1 Introduction\u003cbr\u003e _11.2 Transformers for music generation\u003cbr\u003e _11.3 MuseGAN\u003cbr\u003e _11.4 Summary\u003cbr\u003e\u003cbr\u003e CHAPTER 12 World Model\u003cbr\u003e _12.1 Introduction\u003cbr\u003e _12.2 Reinforcement Learning\u003cbr\u003e _12.3 World Model Overview\u003cbr\u003e _12.4 Random Rollout Data Collection\u003cbr\u003e _12.5 VAE Training\u003cbr\u003e _12.6 Collecting MDN-RNN training data\u003cbr\u003e _12.7 MDN-RNN Training\u003cbr\u003e _12.8 Controller Training\u003cbr\u003e _12.9 Training in Dreams\u003cbr\u003e _12.10 Summary\u003cbr\u003e\u003cbr\u003e CHAPTER 13 Multimodal Models\u003cbr\u003e _13.1 Introduction\u003cbr\u003e _13.2 DALL?E 2\u003cbr\u003e _13.3 Imagen\u003cbr\u003e _13.4 Stable Diffusion\u003cbr\u003e _13.5 Flamingo\u003cbr\u003e _13.6 Summary\u003cbr\u003e\u003cbr\u003e CHAPTER 14 CONCLUSION\u003cbr\u003e _14.1 Timeline of Generated AI\u003cbr\u003e _14.2 Current State of Generative AI\u003cbr\u003e _14.3 The Future of Generative AI\u003cbr\u003e _14.4 Final Comments\u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eDetailed image\u003c\/b\u003e \u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cdiv\u003e\u003cimg src=\"https:\/\/image.yes24.com\/momo\/TopCate4290\/MidCate007\/428965323.jpg\" border=\"0\" alt=\"Detailed Image 1\"\u003e\u003c\/div\u003e\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003ePublisher's Review\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e \u003cb\u003ePart 2 of \"GAN Deep Learning in the Art Museum: A Practical Project\"\u003cbr\u003e The past, present, and future of generative AI that changed the world.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e David Foster is back, explaining generative AI clearly and persuasively. \u003cbr\u003eThe first edition of this book, \"GAN Deep Learning Practical Project for Art Museums,\" focused on GANs, but the field of generative AI has advanced significantly since its publication.\u003cbr\u003e We've updated the 2nd edition to capture the dazzling advancements in generative AI that have astonished the world.\u003cbr\u003e We've updated the existing content with the latest technical information, added more detailed transformer descriptions, and added new multimodal model content.\u003cbr\u003e The upgraded second edition is now available under the new name, \"Learning Generative AI by Creating,\" as it doesn't cover content specific to GANs.\u003cbr\u003e\u003cbr\u003e Armed with cutting-edge technology, this book will transform you into a generative AI expert, complete with engaging stories, practical examples, and practical applications.\u003cbr\u003e Learn how to use the most advanced computer-aided creative techniques.\u003cbr\u003e It's okay if you have no experience with generative AI. \u003cbr\u003eWe will guide you step by step from the beginning so that you can learn the skills.\u003cbr\u003e All you need is some Python coding experience.\u003cbr\u003e After understanding the fundamentals of generative models, learn generative AI by coding directly with Python and Keras.\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e \u003cb\u003eWhat's changed in the 2nd edition\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e -Chapter 1 introduces various generative models and contains a classification system that shows their relationships.\u003cbr\u003e -Chapter 2 has improved illustrations and explains key concepts in more detail.\u003cbr\u003e -Chapter 3 contains new examples and explanations.\u003cbr\u003e -Chapter 4 explains the conditional GAN ​​architecture.\u003cbr\u003e -Chapter 5 describes autoregressive models for images (e.g., PixelCNN).\u003cbr\u003e -Chapter 6 is a completely new chapter, explaining the RealNVP model.\u003cbr\u003e -Chapter 7 is also new and focuses on techniques such as Langevin dynamics and contrastive divergence. \u003cbr\u003e-Chapter 8 is a newly written chapter for noise-removing diffusion models, which form the basis of many modern applications today.\u003cbr\u003e -Chapter 9 expands on the last chapter of the first edition, providing in-depth coverage of various StyleGAN model architectures and new content on VQ-GAN.\u003cbr\u003e -Chapter 10 is a new chapter that takes a closer look at the transformer architecture.\u003cbr\u003e -Chapter 11 covers the latest transformer architecture, replacing the LSTM model from the first edition.\u003cbr\u003e -Chapter 12 has updated illustrations and explanations, and introduces how this approach influences today's state-of-the-art reinforcement learning.\u003cbr\u003e -Chapter 13 is a new chapter that details how impressive models such as DALL·E 2, Imagen, Stable Diffusion, and Flamingo work.\u003cbr\u003e Chapter 14 reflects the remarkable progress made in generative AI since the first edition and provides a more complete and detailed view of where things are headed next.\u003cbr\u003e\u003cbr\u003e \u003cb\u003eTarget audience\u003c\/b\u003e\u003cbr\u003e \u003cbr\u003e- Undergraduate students and developers who want to understand how generative AI works and try using it themselves.\u003cbr\u003e Machine learning engineers, data scientists, and researchers interested in the latest deep learning technologies.\u003cbr\u003e\u003cbr\u003e \u003cb\u003eKey Contents\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e -Change facial expressions in photos with VAE\u003cbr\u003e - Generating images using a GAN trained on its own dataset.\u003cbr\u003e -Creating new flower types using a diffusion model\u003cbr\u003e -Training your own GPT for text generation\u003cbr\u003e Learn how to train ChatGPT, a large-scale language model.\u003cbr\u003e -Investigate state-of-the-art architectures such as StyleGAN2 and ViT VQ-GAN.\u003cbr\u003e -Composing polyphonic music using Transformers and MuseGAN\u003cbr\u003e - Understand how world models solve reinforcement learning tasks.\u003cbr\u003e -Learn about multimodal models such as DALL·E 2, Imagen, and Stable Diffusion. \u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e GOODS SPECIFICS \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eDate of issue:\u003c\/strong\u003e September 15, 2023\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003ePage count, weight, size:\u003c\/strong\u003e 480 pages | 1,195g | 183*235*30mm\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN13:\u003c\/strong\u003e 9791169211437\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN10:\u003c\/strong\u003e 1169211437 \u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cspan\u003e\u003c\/span\u003e\n\n\u003c\/center\u003e\n\n\n\u003c\/center\u003e","brand":"LIBRAIRIE COREENNE","offers":[{"title":"Default Title","offer_id":43893225488426,"sku":"138268","price":52.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0683\/2750\/5962\/files\/f485f957c0347eec306fdba714cd054a.jpg?v=1765392524","url":"https:\/\/librairie.coreenne.fr\/en\/products\/138268","provider":"LIBRAIRIE COREENNE","version":"1.0","type":"link"}