Using generative ai effectively in higher education,
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
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.
Название: Generative AI in Higher Education ISBN: 1032599049 ISBN-13(EAN): 9781032599045 Издательство: Taylor&Francis Рейтинг: Цена: 35720.00 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: Agkathidis, Asterios Название: Ai-assisted architectural design ISBN: 906369704X ISBN-13(EAN): 9789063697044 Издательство: Laurence King Рейтинг: Цена: 14160.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Название: Generative ai security ISBN: 3031542517 ISBN-13(EAN): 9783031542510 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Partha Niyogi Название: The Informational Complexity of Learning ISBN: 1461374936 ISBN-13(EAN): 9781461374930 Издательство: Springer Рейтинг: Цена: 93160.00 T 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: Parra Pennefather Название: Creative Prototyping with Generative AI ISBN: 1484295781 ISBN-13(EAN): 9781484295786 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Reimagine different generative AI as useful creative prototyping tools that can be used to augment your own creative process and projects. Gain a deeper understanding of how generative AI can elevate your creative future. You will acquire a comprehensive understanding of how AI works, uncover tools that can enhance your AI interactions, learn how to extract maximum potential from AI-produced content, and experiment with methods for assessing, refining, and boosting the content to transform your creative projects. You'll also explore how creative professionals from varied disciplines are employing generative AI in their workflows to produce distinctive contributions to the world. Each chapter provides examples of how designers and other creative individuals can utilize these technological wonders, adopting various prototyping techniques to fast-track and optimize design processes and workflows. Creators from all disciplines can tap into the vast capabilities and benefits of generative AI, enabling them to rapidly experiment and prototype their ideas. You Will Learn: * Understand how generative AI can support your own creative process * Learn tools to get the most out of text-text, text-image, and text-video generative AI * Augment your design practices using generative AI * Draw inspiration from AI generated content to create unique creative work * Improve and streamline creatives processes and workflows Who This Book Is For * Digital media professionals who want to access off-the shelf creative tools to improve and accelerate their creativity and workflow. * Designers and engineers who are looking at novel ways to improve their prototyping and testing processes. * Students who want to use AI to rapidly generate ideas to support them in prototyping assignments. * Instructors interested in pointing their students to a variety of accessible AI resources to manage their own creativity.
Автор: Kulkarni Название: Applied Generative AI for Beginners ISBN: 1484299930 ISBN-13(EAN): 9781484299937 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a deep dive into the world of generative AI, covering everything from the basics of neural networks to the intricacies of large language models like ChatGPT and Google Bard. It serves as a one-stop resource for anyone interested in understanding and applying this transformative technology and is particularly aimed at those just getting started with generative AI. Applied Generative AI for Beginners is structured around detailed chapters that will guide you from foundational knowledge to practical implementation. It starts with an introduction to generative AI and its current landscape, followed by an exploration of how the evolution of neural networks led to the development of large language models. The book then delves into specific architectures like ChatGPT and Google Bard, offering hands-on demonstrations for implementation using tools like Sklearn. You’ll also gain insight into the strategic aspects of implementing generative AI in an enterprise setting, with the authors covering crucial topics such as LLMOps, technology stack selection, and in-context learning. The latter part of the book explores generative AI for images and provides industry-specific use cases, making it a comprehensive guide for practical application in various domains. Whether you're a data scientist looking to implement advanced models, a business leader aiming to leverage AI for enterprise growth, or an academic interested in cutting-edge advancements, this book offers a concise yet thorough guide to mastering generative AI, balancing theoretical knowledge with practical insights. What You Will Learn * Gain a solid understanding of generative AI, starting from the basics of neural networks and progressing to complex architectures like ChatGPT and Google Bard * Implement large language models using Sklearn, complete with code examples and best practices for real-world application * Learn how to integrate LLM’s in enterprises, including aspects like LLMOps and technology stack selection * Understand how generative AI can be applied across various industries, from healthcare and marketing to legal compliance through detailed use cases and actionable insights Who This Book Is For Data scientists, AI practitioners, Researchers and software engineers interested in generative AI and LLMs.
Автор: Mukhopadhyay Название: Deep Generative Models ISBN: 3031537661 ISBN-13(EAN): 9783031537660 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
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