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: 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: Bernd Mohr; Jesper Larsson Tr?ff; Joachim Worringe Название: Recent Advances in Parallel Virtual Machine and Message Passing Interface ISBN: 354039110X ISBN-13(EAN): 9783540391104 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the 13th European PVM/MPI Users` Group Meeting, held in September 2006. This book contains papers that are organized in topical sections on collective communication, communication protocols, debugging and verification, fault tolerance, metacomputing and grid, parallel I/O, and implementation issues.
Автор: Beniamino Di Martino; Dieter Kranzlm?ller; Jack Do Название: Recent Advances in Parallel Virtual Machine and Message Passing Interface ISBN: 3540290095 ISBN-13(EAN): 9783540290094 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the proceedings of the 12th European PVM/MPI Users` Group Meeting held in Sorrento, Italy in September 2005. This book includes 61 papers, which are organized in topical sections on algorithms, extensions and improvements, cluster and grid, tools and environments, performance, applications and ParSim 2005.
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.
Описание: Constitutes the refereed proceedings of the 14th European PVM/MPI Users` Group Meeting held in Paris, France, September 30 - October 3, 2007. This book presents 40 revised full papers together with abstracts of 6 invited contributions, 3 tutorial papers and 6 poster papers that were reviewed and selected from 68 submissions.
Описание: Covers the proceedings of the 15th European PVM/MPI Users` Group Meeting held in Dublin, Ireland, in September 2008. This book contains topical sections on applications, collective operations, library internals, message passing for multi-core and mutlithreaded architectures, MPI datatypes, MPI I/O, and synchronisation issues.
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Описание: This book constitutes the refereed proceedings of the 16th European PVM/MPI Users` Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface, EuroPVM/MPI 2009, held in Espoo, Finland, September 7-10, 2009.
Автор: Christoph Guger; Brendan Allison; E.C. Leuthardt Название: Brain-Computer Interface Research ISBN: 3642547060 ISBN-13(EAN): 9783642547065 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It introduces ten outstanding and innovative BCI projects, nominated as finalists for the BCI award 2012 by a jury of established researchers and discusses how each of the nominated projects reflects general worldwide trends in BCI development.
Автор: Guger Christoph Название: Brain-computer-interface Research ISBN: 3642360823 ISBN-13(EAN): 9783642360824 Издательство: Springer Рейтинг: Цена: 8489.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Brain-computer interfaces (BCIs) are rapidly developing into a mainstream, worldwide research endeavor. This Brief gives a concise but carefully illustrated and fully up-to-date description of each of these projects, together with an introduction and concluding chapter by the editors.
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