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Handbook of Big Data, Peter Buhlmann, Petros Drineas, Michael Kane, Mark van der Laan


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Автор: Peter Buhlmann, Petros Drineas, Michael Kane, Mark van der Laan
Название:  Handbook of Big Data
ISBN: 9780367330736
Издательство: Taylor&Francis
Классификация:


ISBN-10: 0367330733
Обложка/Формат: Paperback
Страницы: 480
Вес: 1.95 кг.
Дата издания: 18.06.2019
Серия: Chapman & hall/crc handbooks of modern statistical methods
Язык: English
Иллюстрации: 41 illustrations, color; 56 illustrations, black and white
Размер: 266 x 254 x 25
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Probability & statistics, BUSINESS & ECONOMICS / Statistics,COMPUTERS / Machine Theory,MATHEMATICS / Probability & Statistics / General
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Поставляется из: Европейский союз
Описание: This handbook provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from statistics and computer science experts in industry and academia, the text instills a working understanding of key statistical and computing ideas that can be readily applied in research and practice.

Optical Properties of Diamond / A Data Handbook

Автор: Zaitsev A.M.
Название: Optical Properties of Diamond / A Data Handbook
ISBN: 354066582X ISBN-13(EAN): 9783540665823
Издательство: Springer
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Цена: 260870.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This handbook is the most comprehensive compilation of data on the optical properties of diamond ever written. It presents a multitude of data previously for the first time in English. The author provides quick access to the most comprehensive information on all aspects of the field.

Handbook of Big Data Analytics

Автор: Wolfgang Karl H?rdle; Henry Horng-Shing Lu; Xiaoto
Название: Handbook of Big Data Analytics
ISBN: 3319182838 ISBN-13(EAN): 9783319182834
Издательство: Springer
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Цена: 260870.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.

Handbook for Applied Modeling: Non-Gaussian and Correlated Data

Автор: Jamie D. Riggs
Название: Handbook for Applied Modeling: Non-Gaussian and Correlated Data
ISBN: 1316601056 ISBN-13(EAN): 9781316601051
Издательство: Cambridge Academ
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Цена: 40130.00 T
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Описание: Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing data that fail idealized assumptions. It explains and demonstrates core techniques, common pitfalls and data issues, and interpretation of model results, all with a focus on application, utility, and real-life data.

Handbook of Statistical Analysis and Data Mining Applications, 2 ed.

Автор: Robert Nisbet , Gary Miner, Ken Yale
Название: Handbook of Statistical Analysis and Data Mining Applications, 2 ed.
ISBN: 0124166326 ISBN-13(EAN): 9780124166325
Издательство: Elsevier Science
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Цена: 88690.00 T
Наличие на складе: Нет в наличии.
Описание:

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application.

This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas--from science and engineering, to medicine, academia and commerce.

  • Includes input by practitioners for practitioners
  • Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models
  • Contains practical advice from successful real-world implementations
  • Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions
  • Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Computational Statistics Handbook with MATLAB

Автор: Martinez Wendy L.
Название: Computational Statistics Handbook with MATLAB
ISBN: 1466592737 ISBN-13(EAN): 9781466592735
Издательство: Taylor&Francis
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Цена: 107190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

A Strong Practical Focus on Applications and Algorithms
Computational Statistics Handbook with MATLAB(R), Third Edition covers today's most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. The text keeps theoretical concepts to a minimum, emphasizing the implementation of the methods.

New to the Third Edition
This third edition is updated with the latest version of MATLAB and the corresponding version of the Statistics and Machine Learning Toolbox. It also incorporates new sections on the nearest neighbor classifier, support vector machines, model checking and regularization, partial least squares regression, and multivariate adaptive regression splines.

Web Resource
The authors include algorithmic descriptions of the procedures as well as examples that illustrate the use of algorithms in data analysis. The MATLAB code, examples, and data sets are available online.



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