Digital Geometry Algorithms, Valentin E. Brimkov; Reneta P. Barneva
Автор: David J. C. MacKay Название: Information Theory, Inference and Learning Algorithms ISBN: 0521642981 ISBN-13(EAN): 9780521642989 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This exciting and entertaining textbook is ideal for courses in information, communication and coding. It is an unparalleled entry point to these subjects for professionals working in areas as diverse as computational biology, data mining, financial engineering and machine learning.
Автор: Sung Название: Algorithms in Bioinformatics ISBN: 1420070339 ISBN-13(EAN): 9781420070330 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents an introduction to the algorithmic techniques applied in bioinformatics. For each topic, this title details the biological motivation, defines the corresponding computational problems, and includes examples to illustrate each algorithm.
Автор: Lee Lanier Название: Digital Compositing with Nuke, ISBN: 0240820355 ISBN-13(EAN): 9780240820354 Издательство: Taylor&Francis Рейтинг: Цена: 7654.00 р. Наличие на складе: Поставка под заказ.
Описание: For novice compositors and veterans moving over from Shake or After Effects, this book is the essential guide for learning Nuke, the powerful, node-based compositing software and standard choice for the VFX industry. It provides a complete overview of the Nuke software, from an introduction to the user interface to more complex compositing tasks.
Автор: Mukhopadhyay Sambit, Morris Edward, Arulkumaran Sa Название: Algorithms for Obstetrics and Gynaecology ISBN: 0199651396 ISBN-13(EAN): 9780199651399 Издательство: Oxford Academ Рейтинг: Цена: 7760.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Algorithms in Obstetrics and Gynaecology presents the core knowledge needed to tackle all situations in obstetrics and gynaecology, in a structured fashion. All algorithms are designed to support rapid decision making in the most clinically relevant situations to minimise the risks of a poor outcome.
Автор: Alicia Dickenstein; Frank-Olaf Schreyer; Andrew J. Название: Algorithms in Algebraic Geometry ISBN: 144192583X ISBN-13(EAN): 9781441925831 Издательство: Springer Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
In the last decade, there has been a burgeoning of activity in the design and implementation of algorithms for algebraic geometric computation. The workshop on Algorithms in Algebraic Geometry that was held in the framework of the IMA Annual Program Year in Applications of Algebraic Geometry by the Institute for Mathematics and Its Applications on September 2006 is one tangible indication of the interest. This volume of articles captures some of the spirit of the IMA workshop.
Описание: This monograph studies the theoretical complexity and practical efficiency of randomized dynamic algorithms.
Автор: Hanspeter Bieri; Hartmut Noltemeier Название: Computational Geometry - Methods, Algorithms and Applications ISBN: 3540548912 ISBN-13(EAN): 9783540548911 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents the proceedings of the Seventh International Workshop on Computational Geometry. Topics include: the Voronoi diagram, rectangular objects, path determination, moving objects, visibility questions, layout problems, spatial objects and queries, higher dimensions, implementation, and relations to AI.
Автор: Saugata Basu; Richard Pollack; Marie-Fran?oise Cos Название: Algorithms in Real Algebraic Geometry ISBN: 3642069649 ISBN-13(EAN): 9783642069642 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The algorithmic problems of real algebraic geometry such as real root counting, deciding the existence of solutions of systems of polynomial equations and inequalities, finding global maxima or deciding whether two points belong in the same connected component of a semi-algebraic set appear frequently in many areas of science and engineering. In this textbook the main ideas and techniques presented form a coherent and rich body of knowledge.
Mathematicians will find relevant information about the algorithmic aspects. Researchers in computer science and engineering will find the required mathematical background.
Being self-contained the book is accessible to graduate students and even, for invaluable parts of it, to undergraduate students.
This second edition contains several recent results, on discriminants of symmetric matrices, real root isolation, global optimization, quantitative results on semi-algebraic sets and the first single exponential algorithm computing their first Betti number.
Автор: Nancy A. Lynch Название: Distributed Algorithms, ISBN: 1558603484 ISBN-13(EAN): 9781558603486 Издательство: Elsevier Science Рейтинг: Цена: 20549.00 р. Наличие на складе: Поставка под заказ.
Описание: A guide to designing, implementing and analyzing distributed algorithms. It covers problems including resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election and global snapshots.
Автор: Edelsbrunner Название: Algorithms in combinatorial geometry ISBN: 354013722X ISBN-13(EAN): 9783540137221 Издательство: Springer Рейтинг: Цена: 18161.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a modern approach to computational geo- metry, an area thatstudies the computational complexity of geometric problems. Combinatorial investigations play an important role in this study.
Автор: S.T. Chadradhar; Vishwani Agrawal; M. Bushnell Название: Neural Models and Algorithms for Digital Testing ISBN: 0792391659 ISBN-13(EAN): 9780792391654 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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