Описание: In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data.
Описание: This book features papers on implementing intelligent tools for building a scientific information platform. It covers architecture of scientific information platforms, semantic clustering, ontology-based systems and multimedia data processing.
Artificial intelligence will radically change our lives--just not in the ways you might think.
You've been made to believe that AI will take your job. The truth is AI will deeply change the nature of work itself and lead to the creation of jobs that don't exist yet.
Sensational media reports speculate about the "rise of the machines" but fail to see that there's no real intelligence in AI. It is not an all-seeing master, but rather a functional tool that must combine with the intelligence we possess to be effective.
With The AI Republic, Terence Tse, Mark Esposito, and Danny Goh have not written a book for coders, but for everyone curious about a future shaped by AI. They demystify this life-changing technology and explain how we can build a shared space where humans and intelligent automation work together, whether you're a business executive who wants to implement it, a government leader responsible for policy creation, or a parent who wants to prepare your children to grow up with AI as a companion.
Описание: This book is among the very few to be entirely dedicated to the treatment of knowledge imperfection when building intelligent systems. The authors are of the belief that an entire book should be focused on this important aspect of knowledge processing.
Автор: Thomas D. Feigenbaum Название: Building Intelligent Information Systems Software ISBN: 0128051019 ISBN-13(EAN): 9780128051016 Издательство: Elsevier Science Рейтинг: Цена: 6990.00 р. Наличие на складе: Поставка под заказ.
Описание: "
Building Intelligent Information Systems Software "shows scientists and engineers how to build applications that model complex information, data, and knowledge without the need for coding. Traditional software development takes time and leads to inflexible, complicated applications that almost, but don t exactly, meet the intended needs. Requirements can change, sometimes mid-development, and adapting existing systems can be difficult. Individual solutions can be incompatible, leading to information silos and inefficiency throughout an organization. This book offers a solution the Information Unit Model, an innovative architecture for translating domain knowledge into applications. By encapsulating the complexities of computing, the Unit Model allows engineers to focus on business or experimental needs. Author Tom Feigenbaum, inventor of the Unit Modeler, demonstrates this innovative software architecture for rapid application design and development. His approach promotes repurposing pre-existing tools and libraries, and collaborating across the cloud, to promote information sharing and efficient development practices. Each concept is illustrated with examples including file management, data management, and 3D visualization. Turn your domain knowledge into applications without heavy coding Design and develop information systems applications in a fraction of the time of traditional methodsLeverage previously-built components to jump start new projectsIncludes access to a trial version of the Information Unit Modeler tool for rapid application development"
Автор: Sergio Escalera; Markus Weimer Название: The NIPS `17 Competition: Building Intelligent Systems ISBN: 3319940414 ISBN-13(EAN): 9783319940410 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book summarizes the organized competitions held during the first NIPS competition track. It provides both theory and applications of hot topics in machine learning, such as adversarial learning, conversational intelligence, and deep reinforcement learning.Rigorous competition evaluation was based on the quality of data, problem interest and impact, promoting the design of new models, and a proper schedule and management procedure. This book contains the chapters from organizers on competition design and from top-ranked participants on their proposed solutions for the five accepted competitions: The Conversational Intelligence Challenge, Classifying Clinically Actionable Genetic Mutations, Learning to Run, Human-Computer Question Answering Competition, and Adversarial Attacks and Defenses.
Описание: This book presents recent research in intelligent information and database systems. The carefully selected contributions were initially accepted for presentation as posters at the 9th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2017) held from to 5 April 2017 in Kanazawa, Japan. While the contributions are of an advanced scientific level, several are accessible for non-expert readers.
The book brings together 47 chapters divided into six main parts:* Part I. From Machine Learning to Data Mining.* Part II. Big Data and Collaborative Decision Support Systems,* Part III.
Computer Vision Analysis, Detection, Tracking and Recognition,* Part IV. Data-Intensive Text Processing,* Part V. Innovations in Web and Internet Technologies, and* Part VI.
New Methods and Applications in Information and Software Engineering. The book is an excellent resource for researchers and those working in algorithmics, artificial and computational intelligence, collaborative systems, decision management and support systems, natural language processing, image and text processing, Internet technologies, and information and software engineering, as well as for students interested in such research areas.
Автор: Sabu M. Thampi; Sushmita Mitra; Jayanta Mukhopadhy Название: Intelligent Systems Technologies and Applications ISBN: 3319683845 ISBN-13(EAN): 9783319683843 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the thoroughly refereed post-conference proceedings of the third International Symposium on Intelligent Systems Technologies and Applications (ISTA`17), September 13-16, 2017, Manipal, Karnataka, India. This proceedings contains 34 papers selected for presentation at the Symposium.
Автор: Robert Bembenik; Lukasz Skonieczny; Henryk Rybi?sk Название: Intelligent Tools for Building a Scientific Information Platform ISBN: 3642442285 ISBN-13(EAN): 9783642442285 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In an economic environment full of turmoil, the more versatile our explanatory models the better. This volume widens our perspective on these matters with innovative research on the application of pretopology and topology to economics and management studies.
Описание: This book features papers on implementing intelligent tools for building a scientific information platform. It covers architecture of scientific information platforms, semantic clustering, ontology-based systems and multimedia data processing.
Автор: Sergio Escalera; Markus Weimer Название: The NIPS `17 Competition: Building Intelligent Systems ISBN: 3030068676 ISBN-13(EAN): 9783030068677 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Поставка под заказ.
Описание: This book summarizes the organized competitions held during the first NIPS competition track. It provides both theory and applications of hot topics in machine learning, such as adversarial learning, conversational intelligence, and deep reinforcement learning.Rigorous competition evaluation was based on the quality of data, problem interest and impact, promoting the design of new models, and a proper schedule and management procedure. This book contains the chapters from organizers on competition design and from top-ranked participants on their proposed solutions for the five accepted competitions: The Conversational Intelligence Challenge, Classifying Clinically Actionable Genetic Mutations, Learning to Run, Human-Computer Question Answering Competition, and Adversarial Attacks and Defenses.
Автор: Judea Pearl Название: Probabilistic Reasoning in Intelligent Systems, ISBN: 1558604790 ISBN-13(EAN): 9781558604797 Издательство: Elsevier Science Рейтинг: Цена: 9599.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic.
The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information.
Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
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