Автор: Christopher M. Bishop Название: Pattern Recognition and Machine Learning ISBN: 0387310738 ISBN-13(EAN): 9780387310732 Издательство: Springer Рейтинг: Цена: 11878.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Автор: Dummit, David S. Foote, Richard M. Название: Abstract Algebra, 3rd Edition ISBN: 0471433349 ISBN-13(EAN): 9780471433347 Издательство: Wiley Рейтинг: Цена: 21376.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Widely acclaimed algebra text. This book is designed to give the reader insight into the power and beauty that accrues from a rich interplay between different areas of mathematics.
Автор: Boothroyd, G. Название: Fundamentals of machining and machine tools ISBN: 1574446592 ISBN-13(EAN): 9781574446593 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reflecting changes in machining practice, Fundamentals of Machining and Machine Tools, Third Edition emphasizes the economics of machining processes and design for machining. This edition includes new material on super-hard cutting tool materials, tool geometries, and surface coatings. It describes recent developments in high-speed machining, hard machining, and cutting fluid applications such as dry and minimum-quantity lubrication machining. It presents analytical methods that outline the limitations of various appaches. This edition also features expanded information on tool geometries for chip breaking and control as well as improvements in cost modeling of machining processes.
Автор: Cheetham Название: Abstract Art Against Autonomy ISBN: 1107693985 ISBN-13(EAN): 9781107693982 Издательство: Cambridge Academ Рейтинг: Цена: 5069.00 р. Наличие на складе: Поставка под заказ.
Описание: In Abstract Art Against Autonomy, Mark Cheetham provides a revolutionary account of abstraction in the visual arts since the decline of the formalist paradigms in the 1960s. By examining abstract art since the 1960s within a narrative of infection, resistance and cure, Cheetham provides an opportunity to rethink paradigmatic genres.
A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.
Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.
After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.
Автор: Sul Название: Control of Electric Machine Drive Systems ISBN: 0470590793 ISBN-13(EAN): 9780470590799 Издательство: Wiley Рейтинг: Цена: 20901.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Based on the author`s industry experience and collaborative works with other industries, Control of Electric Machine Drive System is packed with implemented, tested, and verified ideas that relate to everyday problems in the field.
Автор: Barber Название: Bayesian Reasoning and Machine Learning ISBN: 0521518148 ISBN-13(EAN): 9780521518147 Издательство: Cambridge Academ Рейтинг: Цена: 11088.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This practical introduction for final-year undergraduate and graduate students is ideally suited to computer scientists without a background in calculus and linear algebra. Numerous examples and exercises are provided. Additional resources available online and in the comprehensive software package include computer code, demos and teaching materials for instructors.
Автор: Jennings Gabrielle Название: Abstract Video: The Moving Image in Contemporary Art ISBN: 0520282485 ISBN-13(EAN): 9780520282483 Издательство: Wiley Рейтинг: Цена: 4752.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Offering historical and theoretical positions from a variety of art historians, artists, curators, and writers, this book addresses a longer history of experimentation in video, net art, installation, new media, expanded cinema, visual music, and experimental film.
Автор: Hackett Название: Psychology and Philosophy of Abstract Art ISBN: 1137483318 ISBN-13(EAN): 9781137483317 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book examines how we perceive and understand abstract art in contrast to artworks that represent reality. Philosophical, psychological and neuroscience research, including the work of philosopher Paul Crowther, are considered and out of these approaches a complex model is developed to account for this experience. The understanding embodied in this model is rooted in facet theory, mapping sentences and partially ordered analyses, which together provide a comprehensive understanding of the perceptual experience of abstract art.
Описание: Like the popular second edition, Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining?including both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. <br><br>Complementing the book is a fully functional platform-independent open source Weka software for machine learning, available for free download. <br><br>The book is a major revision of the second edition that appeared in 2005. While the basic core remains the same, it has been updated to reflect the changes that have taken place over the last four or five years. The highlights for the updated new edition include completely revised technique sections; new chapter on Data Transformations, new chapter on Ensemble Learning, new chapter on Massive Data Sets, a new ?book release? version of the popular Weka machine learning open source software (developed by the authors and specific to the Third Edition); new material on ?multi-instance learning?; new information on ranking the classification, plus comprehensive updates and modernization throughout. All in all, approximately 100 pages of new material.<br> <br><br>* Thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques<br><br>* Algorithmic methods at the heart of successful data mining?including tired and true methods as well as leading edge methods<br><br>* Performance improvement techniques that work by transforming the input or output<br><br>* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization?in an updated, interactive interface. <br>
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