Mathematics Education in the Age of Artificial Intelligence, Richard
Автор: Low Emma Название: Cambridge Primary Mathematics Stage 6 Learner`s Book ISBN: 1107618592 ISBN-13(EAN): 9781107618596 Издательство: Cambridge Education Рейтинг: Цена: 2995.00 р. Наличие на складе: Есть (более 5-х шт.) Описание: This series is endorsed by Cambridge International Examinations and is part of Cambridge Maths. Children will enjoy learning mathematics with this fun and attractive learner's book for stage 6. A variety of questions, activities, investigations and games that are designed to reinforce the concepts learnt in the core activities in the teacher's guide and address misconceptions are included along with hints and tips. Clear, often pictorial, explanation of mathematical vocabulary will help children learn new terms whether they are native English speakers or second language speakers and great care has been made to ensure language is accessible.
Автор: Koushik Ghosh, Souvik Bhattacharyya Название: Noise Filtering for Big Data Analytics ISBN: 3110697092 ISBN-13(EAN): 9783110697094 Издательство: Walter de Gruyter Рейтинг: Цена: 26024.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model.
Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information.
This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.
Without mathematics no science would survive. This especially applies to the engineering sciences which highly depend on the applications of mathematics and mathematical tools such as optimization techniques, finite element methods, differential equations, fluid dynamics, mathematical modelling, and simulation. Neither optimization in engineering, nor the performance of safety-critical system and system security; nor high assurance software architecture and design would be possible without the development of mathematical applications.
De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences (AMEIS) focusses on the latest applications of engineering and information technology that are possible only with the use of mathematical methods. By identifying the gaps in knowledge of engineering applications the AMEIS series fosters the international interchange between the sciences and keeps the reader informed about the latest developments.
Автор: Copeland, B. Jack. Название: The Essential Turing ISBN: 0198250800 ISBN-13(EAN): 9780198250807 Издательство: Oxford Academ Рейтинг: Цена: 5542.00 р. Наличие на складе: Есть (1 шт.) Описание: The ideas that gave birth to the computer age Alan Turing, pioneer of computing and World War II codebreaker, was one of the most important and influential thinkers of the twentieth century. This volume presents his key writings that deals with: computational theory, cognitive science, artificial intelligence, and artificial life.
Автор: Paris Название: Pure Inductive Logic ISBN: 1107042305 ISBN-13(EAN): 9781107042308 Издательство: Cambridge Academ Рейтинг: Цена: 21226.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book establishes pure inductive logic as a contemporary branch of mathematical logic. Collecting together research from a wide range of sources within one unified context, it provides both a comprehensive account of the subject up to cutting-edge modern research, and an accessible reference for the philosopher or computer scientist.
The monographic volume addresses, in a systematic and comprehensive way, the state-of-the-art dependability (reliability, availability, risk and safety, security) of systems, using the Artificial Intelligence framework of Probabilistic Graphical Models (PGM). After a survey about the main concepts and methodologies adopted in dependability analysis, the book discusses the main features of PGM formalisms (like Bayesian and Decision Networks) and the advantages, both in terms of modeling and analysis, with respect to classical formalisms and model languages.
Methodologies for deriving PGMs from standard dependability formalisms will be introduced, by pointing out tools able to support such a process. Several case studies will be presented and analyzed to support the suitability of the use of PGMs in the study of dependable systems.
Автор: Walton Название: Burden of Proof, Presumption and Argumentation ISBN: 110767882X ISBN-13(EAN): 9781107678828 Издательство: Cambridge Academ Рейтинг: Цена: 3960.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explains how burden of proof and presumption work as powerful devices in argumentation, based on studying many clearly explained legal and non-legal examples.
Автор: van Benthem Название: Logical Dynamics of Information and Interaction ISBN: 1107417171 ISBN-13(EAN): 9781107417175 Издательство: Cambridge Academ Рейтинг: Цена: 7445.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book develops a view of logic as a theory of information-driven agency and intelligent interaction between many agents - with conversation, argumentation and games as guiding examples. It will interest students and scholars in a wide variety of subject areas.
Автор: Walton Название: Methods of Argumentation ISBN: 1107677335 ISBN-13(EAN): 9781107677333 Издательство: Cambridge Academ Рейтинг: Цена: 4435.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book, written by a leading expert, and based on the latest research, shows how to apply methods of argumentation to a range of interesting examples. Written in a nontechnical style, the book explains what you most need to know by applying the methods to many real examples of arguments found in everyday conversational exchanges and legal argumentation.
Автор: Walton Название: Methods of Argumentation ISBN: 1107039304 ISBN-13(EAN): 9781107039308 Издательство: Cambridge Academ Рейтинг: Цена: 12195.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book, written by a leading expert, and based on the latest research, shows how to apply methods of argumentation to a range of interesting examples. Written in a nontechnical style, the book explains what you most need to know by applying the methods to many real examples of arguments found in everyday conversational exchanges and legal argumentation.
Автор: Stephen M. Watt; Alan Sexton; James H. Davenport; Название: Intelligent Computer Mathematics ISBN: 331908433X ISBN-13(EAN): 9783319084336 Издательство: Springer Рейтинг: Цена: 8944.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the joint refereed proceedings of Calculemus 2014, Digital Mathematics Libraries, DML 2014, Mathematical Knowledge Management, MKM 2014 and Systems and Projects, S&P 2014, held in Coimbra, Portugal, during July 7-11, 2014 as four tracks of CICM 2014, the Conferences on Intelligent Computer Mathematics.
Автор: P. Cheeseman; R.W. Oldford Название: Selecting Models from Data ISBN: 0387942815 ISBN-13(EAN): 9780387942810 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume is a selection of papers presented at the Fourth International Workshop on Artificial Intelligence and Statistics held in January 1993. In particular, there is agreement that the fundamental problem is the avoidence of "overfitting"-Le., where a model fits the given data very closely, but is a poor predictor for new data;
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