Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration.
"Computational and Statistical Methods for Analysing Big Data with Applications" starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data.
Advanced computational and statistical methodologies for analysing big data are developed.
Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable.
Case studies are discussed to demonstrate the implementation of the developed methods.
Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation.
Computing code/programs are provided where appropriate.
Автор: Fausto Pedro Garc?a M?rquez; Benjamin Lev Название: Big Data Management ISBN: 3319454978 ISBN-13(EAN): 9783319454979 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on the analytic principles of business practice and big data. Specifically, it provides an interface between the main disciplines of engineering/technology and the organizational and administrative aspects of management, serving as a complement to books in other disciplines such as economics, finance, marketing and risk analysis. The contributors present their areas of expertise, together with essential case studies that illustrate the successful application of engineering management theories in real-life examples.
Автор: Wang Название: Big Data Computing and Communications ISBN: 3319425528 ISBN-13(EAN): 9783319425528 Издательство: Springer Рейтинг: Цена: 8944.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the Second International Conference on Big Data Computing and Communications, BigCom 2016, held in Shenyang, China, in July 2016.
Автор: Hanan Samet Название: Foundations of Multidimensional and Metric Data Structures, ISBN: 0123694469 ISBN-13(EAN): 9780123694461 Издательство: Elsevier Science Рейтинг: Цена: 10441.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Discusses multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets. This book includes a comprehensive survey to spatial and multidimensional data structures and algorithms. It also includes implementation details for some of the most useful data structures.
Автор: Koitzsch Название: Pro Hadoop Data Analytics ISBN: 1484219090 ISBN-13(EAN): 9781484219096 Издательство: Springer Рейтинг: Цена: 5589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Learn advanced analytical techniques and leverage existing toolkits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems which go beyond the basics of classification, clustering, and recommendation.In Pro Hadoop Data Analytics best practices are emphasized to ensure coherent, efficient development. A complete example system will be developed using standard third-party components which will consist of the toolkits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system.The book emphasizes four important topics:The importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. Best practices and structured design principles. This will include strategic topics as well as the how to example portions.The importance of mix-and-match or hybrid systems, using different analytical components in one application to accomplish application goals. The hybrid approach will be prominent in the examples.Use of existing third-party libraries is key to effective development. Deep dive examples of the functionality of some of these toolkits will be showcased as you develop the example system.
What You'll Learn The what, why, and how of building big data analytic systems with the Hadoop ecosystemLibraries, toolkits, and algorithms to make development easier and more effectiveBest practices to use when building analytic systems with Hadoop, and metrics to measure performance and efficiency of components and systemsHow to connect to standard relational databases, noSQL data sources, and moreUseful case studies and example components which assist you in creating your own systems
Who This Book Is For
Software engineers, architects, and data scientists with an interest in the design and implementation of big data analytical systems using Hadoop, the Hadoop ecosystem, and other associated technologies.
Автор: Calheiros, Rodrigo N. Название: Big Data ISBN: 0128053941 ISBN-13(EAN): 9780128053942 Издательство: Elsevier Science Рейтинг: Цена: 10610.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications.
To help realize Big Data's full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues.
Автор: Pardalos Название: Machine Learning, Optimization, and Big Data ISBN: 3319514687 ISBN-13(EAN): 9783319514680 Издательство: Springer Рейтинг: Цена: 9224.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD 2016, held in Volterra, Italy, in August 2016. The 40 papers presented in this volume were carefully reviewed and selected from 97 submissions.
Автор: Tan Название: Data Mining and Big Data ISBN: 3319409727 ISBN-13(EAN): 9783319409726 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The LNCS volume LNCS 9714 constitutes the refereed proceedings of the International Conference on Data Mining and Big Data, DMBD 2016, held in Bali, Indonesia, in June 2016. The 57 papers presented in this volume were carefully reviewed and selected from 115 submissions.
Описание: Complex multivariate testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. As a result, modern statistics needs permutation testing for complex data with low sample size and many variables, especially in observational studies.
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