Topological Data Analysis: The Abel Symposium 2018, Baas Nils A., Carlsson Gunnar E., Quick Gereon
Автор: Jean-Daniel Boissonnat, Frederic Chazal, Mariette Yvinec Название: Geometric and Topological Inference ISBN: 1108419399 ISBN-13(EAN): 9781108419390 Издательство: Cambridge Academ Рейтинг: Цена: 66530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers a rigorous introduction to geometric and topological inference, a rapidly evolving field that intersects computational geometry, applied topology, and data analysis. It can serve as a textbook for graduate students or researchers in mathematics, computer science and engineering interested in a geometric approach to data science.
Автор: Burghelea Dan Название: New Topological Invariants For Real- And Angle-valued Maps: An Alternative To Morse-novikov Theory ISBN: 9814618241 ISBN-13(EAN): 9789814618243 Издательство: World Scientific Publishing Рейтинг: Цена: 72870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents an alternative to what the topologists refer to as "Morse-Novikov theory", a mathematical theory which belongs to the fields of geometry and topology.
Автор: Holmes Название: Introduction to Scientific Computing and Data Analysis ISBN: 331930254X ISBN-13(EAN): 9783319302546 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Невозможна поставка. Описание: This textbook provides and introduction to numerical computing and its applications in science and engineering. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used.
Автор: Steven L. Brunton, J. Nathan Kutz Название: Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control ISBN: 1108422098 ISBN-13(EAN): 9781108422093 Издательство: Amazon Internet Рейтинг: Цена: 0.00 T Наличие на складе: Невозможна поставка. Описание: Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. Aimed at advanced undergraduate and beginning graduate students, this textbook provides an integrated viewpoint that shows how to apply emerging methods from data science, data mining, and machine learning to engineering and the physical sciences.
This book constitutes the refereed proceedings of the 16th International Symposium on Algorithms and Data Structures, WADS, 2019, held in Edmonton, AB, Canada, in August 2019. The 42 full papers presented together with 3 invited lectures, we carefully reviewed and selected from a total of 88 submissions. They present original research on the theory and application of algorithms and data structures in many areas, including combinatorics, computational geometry, databases, graphics, and parallel and distributed computing.
Автор: Frank Hoffmann; David J Hand; Niall M. Adams; Doug Название: Advances in Intelligent Data Analysis ISBN: 3540425810 ISBN-13(EAN): 9783540425816 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume constitutes the refereed proceedings of the 4th International Conference on Intelligent Data Analysis, IDA 2001. Areas covered include: statistics; artificial intelligence; neural networks; machine learning; data mining; and interactive dynamic data visualization.
Автор: Sergei V. Chekanov Название: Numeric Computation and Statistical Data Analysis on the Java Platform ISBN: 3319285297 ISBN-13(EAN): 9783319285290 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics are the key topics of this book. The short Python code examples powered by the Java platform can be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell.
Автор: Ton J. Cleophas; Aeilko H. Zwinderman Название: Clinical Data Analysis on a Pocket Calculator ISBN: 3319271032 ISBN-13(EAN): 9783319271033 Издательство: Springer Рейтинг: Цена: 78350.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers all relevant pocket calculator statistical methods, making it an ideal resource for those who wish to understand statistics but have no time for complex mathematics. It helps facilitate data analysis by detailing pocket calculator methods.
Автор: O`Connor Brian D., Auwera Geraldine Van Название: Genomics Analysis with Spark, Docker, and Clouds: A Guide to Big Data Tools for Genomics Research ISBN: 1491975199 ISBN-13(EAN): 9781491975190 Издательство: Wiley Рейтинг: Цена: 76020.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data in the genomics field is booming. With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra.
Автор: Boissonnat Jean-Daniel Название: Cambridge Texts in Applied Mathematics ISBN: 1108410898 ISBN-13(EAN): 9781108410892 Издательство: Cambridge Academ Рейтинг: Цена: 40130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers a rigorous introduction to geometric and topological inference, a rapidly evolving field that intersects computational geometry, applied topology, and data analysis. It can serve as a textbook for graduate students or researchers in mathematics, computer science and engineering interested in a geometric approach to data science.
Автор: Janert Philipp K. Название: Data Analysis with Open Source Tools ISBN: 0596802358 ISBN-13(EAN): 9780596802356 Издательство: Wiley Рейтинг: Цена: 33780.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Real World Data Analysis shows you how you think about data and the results you want to achieve with it. Author Philipp Janert teaches you how to effectively approach data analysis problems, and how to extract all the available information from your data. This book shows you how to look at the results and know whether they`re meaningful.
This textbook helps future data analysts comprehend aggregation function theory and methods in an accessible way, focusing on a fundamental understanding of the data and summarization tools. Offering a broad overview of recent trends in aggregation research, it complements any study in statistical or machine learning techniques. Readers will learn how to program key functions in R without obtaining an extensive programming background.
Sections of the textbook cover background information and context, aggregating data with averaging functions, power means, and weighted averages including the Borda count. It explains how to transform data using normalization or scaling and standardization, as well as log, polynomial, and rank transforms. The section on averaging with interaction introduces OWS functions and the Choquet integral, simple functions that allow the handling of non-independent inputs. The final chapters examine software analysis with an emphasis on parameter identification rather than technical aspects.
This textbook is designed for students studying computer science or business who are interested in tools for summarizing and interpreting data, without requiring a strong mathematical background. It is also suitable for those working on sophisticated data science techniques who seek a better conception of fundamental data aggregation. Solutions to the practice questions are included in the textbook.
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