Автор: Chen, Pin-yu (research Sta? Member, Ibm Thomas J. Watson Research Center, Yorktown Heights, Ny, Usa) Hsieh, Cho-jui (assistant Professor, Ucla Compute Название: Adversarial robustness for machine learning ISBN: 0128240202 ISBN-13(EAN): 9780128240205 Издательство: Elsevier Science Рейтинг: Цена: 14308.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: He is exactly what this age needs, a real voice of universal spirituality. His appeal is urgent, human and sacred. DAN CRUSEY Sidney, Ohio Each era has its own prophet poets. Russia has been praying and is praying poems by Pushkin, a holy name for every Russian. Ayaz seems to touch us with that sensitivity, inspiring and changing the rhythm of our breathing. SEBARITA KAKHOVSKAYA Ukraine His words transform you through a subtle Alchemy process, and you suddenly travel from a Neophyte to the Connoisseur of Mysteries. His poetry is a gateway to the stars ELLURA ZURIA Rhn, Germany Reading Ayaz is akin to a journey into the
Описание: Focuses on learning vulnerabilities and cyber security. The book gives detail on the new threats and mitigation methods in the cyber security domain, and provides information on the new threats in new technologies such as vulnerabilities in deep learning, data privacy problems with GDPR, and new solutions.
Автор: Taulli Название: Generative AI ISBN: 148429369X ISBN-13(EAN): 9781484293690 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book will show how generative technology works and the drivers. It will also look at the applications – showing what various startups and large companies are doing in the space. There will also be a look at the challenges and risk factors. During the past decade, companies have spent billions on AI. But the focus has been on applying the technology to predictions – which is known as analytical AI. It can mean that you receive TikTok videos that you cannot resist. Or analytical AI can fend against spam or fraud or forecast when a package will be delivered. While such things are beneficial, there is much more to AI. The next megatrend will be leveraging the technology to be creative. For example, you could take a book and an AI model will turn it into a movie – at very little cost. This is all part of generative AI. It’s still in the nascent stages but it is progressing quickly. Generative AI can already create engaging blog posts, social media messages, beautiful artwork and compelling videos. The potential for this technology is enormous. It will be useful for many categories like sales, marketing, legal, product design, code generation, and even pharmaceutical creation. What You Will Learn The importance of understanding generative AI The fundamentals of the technology, like the foundation and diffusion models How generative AI apps work How generative AI will impact various categories like the law, marketing/sales, gaming, product development, and code generation. The risks, downsides and challenges. Who This Book is For Professionals that do not have a technical background. Rather, the audience will be mostly those in Corporate America (such as managers) as well as people in tech startups, who will need an understanding of generative AI to evaluate the solutions.
Автор: Partha Niyogi Название: The Informational Complexity of Learning ISBN: 1461374936 ISBN-13(EAN): 9781461374930 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Among other topics, The Informational Complexity of Learning: Perspectives on Neural Networks and Generative Grammar brings together two important but very different learning problems within the same analytical framework.
Автор: Tomczak Название: Deep Generative Modeling ISBN: 3030931609 ISBN-13(EAN): 9783030931605 Издательство: Springer Рейтинг: Цена: 6986.00 р. 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: Mao Xudong, Li Qing Название: Generative Adversarial Networks for Image Generation ISBN: 981336047X ISBN-13(EAN): 9789813360471 Издательство: Springer Цена: 20962.00 р. Наличие на складе: Поставка под заказ.
Описание: This book is intended for periodontal residents and practicing periodontists who wish to incorporate the principles of moderate sedation into daily practice. Comprehensive airway management and rescue skills are then documented in detail so that the patient may be properly managed in the event that the sedation progresses beyond the intended level.
Автор: Valle Rafael Название: Hands-On Generative Adversarial Networks with Keras ISBN: 1789538203 ISBN-13(EAN): 9781789538205 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book will explore deep learning and generative models, and their applications in artificial intelligence. You will learn to evaluate and improve your GAN models by eliminating challenges that are encountered in real-world applications. You will implement GAN architectures in various domains such as computer vision, NLP, and audio processing
Автор: Hany John, Walters Greg Название: Hands-On Generative Adversarial Networks with PyTorch 1.x ISBN: 1789530512 ISBN-13(EAN): 9781789530513 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book will help you understand how GANs architecture works using PyTorch. You will get familiar with the most flexible deep learning toolkit and use it to transform ideas into actual working codes. You will apply GAN models to areas like computer vision, multimedia and natural language processing using a sample-generation perspective.
Описание: Generative adversarial networks (GANs) were introduced by Ian Goodfellow and his co-authors including Yoshua Bengio in 2014, and were to referred by Yann Lecun (Facebook’s AI research director) as “the most interesting idea in the last 10 years in ML.” GANs’ potential is huge, because they can learn to mimic any distribution of data, which means they can be taught to create worlds similar to our own in any domain: images, music, speech, prose. They are robot artists in a sense, and their output is remarkable – poignant even. In 2018, Christie’s sold a portrait that had been generated by a GAN for $432,000. Although image generation has been challenging, GAN image generation has proved to be very successful and impressive. However, there are two remaining challenges for GAN image generation: the quality of the generated image and the training stability. This book first provides an overview of GANs, and then discusses the task of image generation and the details of GAN image generation. It also investigates a number of approaches to address the two remaining challenges for GAN image generation. Additionally, it explores three promising applications of GANs, including image-to-image translation, unsupervised domain adaptation and GANs for security. This book appeals to students and researchers who are interested in GANs, image generation and general machine learning and computer vision.
Автор: Razavi-Far Roozbeh, Ruiz-Garcia Ariel, Palade Vasile Название: Generative Adversarial Learning: Architectures and Applications ISBN: 3030913899 ISBN-13(EAN): 9783030913892 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Adversarial learning fascinates the attention of machine learning communities across the world in recent years. Generative adversarial networks (GANs), as the main method of adversarial learning, achieve great success and popularity by exploiting a minimax learning concept, in which two networks compete with each other during the learning process. Their key capability is to generate new data and replicate available data distributions, which are needed in many practical applications, particularly in computer vision and signal processing. The book is intended for academics, practitioners, and research students in artificial intelligence looking to stay up to date with the latest advancements on GANs’ theoretical developments and their applications.
Автор: Vorobeychik, Yevgeniy Kantarcioglu, Murat Название: Adversarial Machine Learning ISBN: 3031004523 ISBN-13(EAN): 9783031004520 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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