Law, human creativity and generative artificial intelligence, Kalpokiene, Julija
Автор: Edited By Roshani Raut, Pranav D Pathak, Sachin R Название: Generative Adversarial Networks and Deep Learning Theory and Applications ISBN: 1032068108 ISBN-13(EAN): 9781032068107 Издательство: Taylor&Francis Рейтинг: Цена: 153120.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications.
Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc. Features:Presents a comprehensive guide on how to use GAN for images and videos.
Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GANHighlights the inclusion of gaming effects using deep learning methodsExamines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutionsThe book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum
Автор: Margaret S. Archer Название: Generative Mechanisms Transforming the Social Order ISBN: 3319137727 ISBN-13(EAN): 9783319137728 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume examines how generative mechanisms emerge in the social order and their consequences.
Название: Generative AI in Higher Education ISBN: 1032604182 ISBN-13(EAN): 9781032604183 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Lopez-lira, Alejandro Название: Predictive edge ISBN: 1394242719 ISBN-13(EAN): 9781394242719 Издательство: Wiley Рейтинг: Цена: 28500.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Tomczak Название: Deep Generative Modeling ISBN: 3030931609 ISBN-13(EAN): 9783030931605 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical predictive modeling and brings together supervised learning and unsupervised learning. The resulting paradigm, called deep generative modeling, utilizes the generative perspective on perceiving the surrounding world. It assumes that each phenomenon is driven by an underlying generative process that defines a joint distribution over random variables and their stochastic interactions, i.e., how events occur and in what order. The adjective "deep" comes from the fact that the distribution is parameterized using deep neural networks. There are two distinct traits of deep generative modeling. First, the application of deep neural networks allows rich and flexible parameterization of distributions. Second, the principled manner of modeling stochastic dependencies using probability theory ensures rigorous formulation and prevents potential flaws in reasoning. Moreover, probability theory provides a unified framework where the likelihood function plays a crucial role in quantifying uncertainty and defining objective functions. Deep Generative Modeling is designed to appeal to curious students, engineers, and researchers with a modest mathematical background in undergraduate calculus, linear algebra, probability theory, and the basics in machine learning, deep learning, and programming in Python and PyTorch (or other deep learning libraries). It will appeal to students and researchers from a variety of backgrounds, including computer science, engineering, data science, physics, and bioinformatics, who wish to become familiar with deep generative modeling. To engage the reader, the book introduces fundamental concepts with specific examples and code snippets. The full code accompanying the book is available on github. The ultimate aim of the book is to outline the most important techniques in deep generative modeling and, eventually, enable readers to formulate new models and implement them.
Автор: Ton J?rg Название: New Thinking in Complexity for the Social Sciences and Humanities ISBN: 9401785139 ISBN-13(EAN): 9789401785136 Издательство: Springer Рейтинг: Цена: 153720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book takes the complexity of our real-world complexity not for granted but as a serious topic for our social sciences and humanities. It is about the possibility of learning a new way of thinking about the real complexity of our world and opening up a new way of viewing and doing science. New tools of thinking and a new language for complexity are developed for dealing with the very complexity of the world in which we live.
Автор: Harvard Business Review Mollick, Ethan Cremer, David De Neeley, Tsedal Sinha, Prabhakant Название: Generative ai: the insights you need from harvard business review ISBN: 164782639X ISBN-13(EAN): 9781647826390 Издательство: INGRAM PUBLISHER SERVICES UK Рейтинг: Цена: 21110.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Tony Jebara Название: Machine Learning ISBN: 1461347564 ISBN-13(EAN): 9781461347569 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines.
Автор: Granville,Vincent Название: Synthetic Data And Generative Ai ISBN: 0443218579 ISBN-13(EAN): 9780443218576 Издательство: Elsevier Science Рейтинг: Цена: 135870.00 T Наличие на складе: Нет в наличии.
Автор: Bart van der Sloot Название: Regulating the Synthetic Society: Generative AI, Legal Questions, and Societal Challenges ISBN: 1509974946 ISBN-13(EAN): 9781509974948 Издательство: Bloomsbury Academic Рейтинг: Цена: 73920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This open access book provides an introduction to Generative Artificial Intelligence and 4 cutting-edge technologies that it enables - humanoid robots, deepfakes, augmented reality, and virtual reality. Experts predict that in 5 years’ time, more than 90% of all digital content will be wholly or partially AI generated. In a synthetic society, it may no longer be possible to establish what is real and what is not. Although they are only in their relative infancy, these technologies can already produce content that is indistinguishable from authentic material. The impact of this new reality on democracy, the judicial system, the functioning of the press, as well as on personal relationships, will be unprecedented. The author describes the inner workings of each of these technologies and maps their positive uses in the fields of education, retail and entertainment; conceptualises their negative uses for fraud, deception, exploitation and identity-theft; and explores their deeper effects on the post-truth society, the privatisation of the public sphere, and the loss of individual autonomy and societal trust. The book evaluates how the current European legal paradigm applies to these technologies, focussing on the right to privacy and data protection, intellectual property, freedom of expression, procedural law, tort law, consumer and competition law, and the regulation of AI. It discusses regulatory alternatives to solve existing regulatory gaps and shows that there are no easy answers.The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com.
Автор: Babcock Joseph, Bali Raghav Название: Generative AI with Python and TensorFlow 2: Harness the power of generative models to create images, text, and music ISBN: 1800200889 ISBN-13(EAN): 9781800200883 Издательство: Неизвестно Рейтинг: Цена: 80910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Packed with intriguing real-world projects as well as theory, Generative AI with Python and TensorFlow 2 enables you to leverage artificial intelligence creatively and generate human-like data in the form of speech, text, images, and music.
Казахстан, 010000 г. Астана, проспект Туран 43/5, НП2 (офис 2) ТОО "Логобук" Тел:+7 707 857-29-98 ,+7(7172) 65-23-70 www.logobook.kz
