Computational and Statistical Methods for Analysing Big Data with Applications Book
Score: 5
From 4 Ratings

Computational and Statistical Methods for Analysing Big Data with Applications


  • Author : Shen Liu
  • Publisher : Academic Press
  • Release Date : 2015-11-20
  • Genre: Mathematics
  • Pages : 206
  • ISBN 10 : 9780081006511

DOWNLOAD BOOK
Computational and Statistical Methods for Analysing Big Data with Applications Excerpt :

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

Data Analytics  Computational Statistics  and Operations Research for Engineers Book

Data Analytics Computational Statistics and Operations Research for Engineers


  • Author : Debabrata Samanta
  • Publisher : CRC Press
  • Release Date : 2022-04-05
  • Genre: Technology & Engineering
  • Pages : 296
  • ISBN 10 : 9781000550429

DOWNLOAD BOOK
Data Analytics Computational Statistics and Operations Research for Engineers Excerpt :

With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.

Data Analysis and Applications 3 Book

Data Analysis and Applications 3


  • Author : Andreas Makrides
  • Publisher : John Wiley & Sons
  • Release Date : 2020-06-16
  • Genre: Business & Economics
  • Pages : 262
  • ISBN 10 : 9781786305343

DOWNLOAD BOOK
Data Analysis and Applications 3 Excerpt :

Data analysis as an area of importance has grown exponentially, especially during the past couple of decades. This can be attributed to a rapidly growing computer industry and the wide applicability of computational techniques, in conjunction with new advances of analytic tools. This being the case, the need for literature that addresses this is self-evident. New publications are appearing, covering the need for information from all fields of science and engineering, thanks to the universal relevance of data analysis and statistics packages. This book is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians who have been working at the forefront of data analysis. The chapters included in this volume represent a cross-section of current concerns and research interests in these scientific areas. The material is divided into two parts: Computational Data Analysis, and Classification Data Analysis, with methods for both - providing the reader with both theoretical and applied information on data analysis methods, models and techniques and appropriate applications.

Classification   Big  Data Analysis and Statistical Learning Book

Classification Big Data Analysis and Statistical Learning


  • Author : Francesco Mola
  • Publisher : Springer
  • Release Date : 2018-02-22
  • Genre: Mathematics
  • Pages : 242
  • ISBN 10 : 3319557076

DOWNLOAD BOOK
Classification Big Data Analysis and Statistical Learning Excerpt :

This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pula (Cagliari), Italy, October 8–10, 2015.

Handbook of Big Data Analytics Book

Handbook of Big Data Analytics


  • Author : Wolfgang Karl Härdle
  • Publisher : Springer
  • Release Date : 2018-07-20
  • Genre: Computers
  • Pages : 538
  • ISBN 10 : 9783319182841

DOWNLOAD BOOK
Handbook of Big Data Analytics Excerpt :

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.

Computational and Statistical Methods for Analysing Big Data with Applications Book

Computational and Statistical Methods for Analysing Big Data with Applications


  • Author : Shen Liu
  • Publisher : Academic Press
  • Release Date : 2015-10-15
  • Genre: Uncategoriezed
  • Pages : 206
  • ISBN 10 : 0128037326

DOWNLOAD BOOK
Computational and Statistical Methods for Analysing Big Data with Applications Excerpt :

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.

Computational Methods for Data Analysis Book

Computational Methods for Data Analysis


  • Author : Yeliz Karaca
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release Date : 2018-12-17
  • Genre: Mathematics
  • Pages : 395
  • ISBN 10 : 9783110493603

DOWNLOAD BOOK
Computational Methods for Data Analysis Excerpt :

This graduate text covers a variety of mathematical and statistical tools for the analysis of big data coming from biology, medicine and economics. Neural networks, Markov chains, tools from statistical physics and wavelet analysis are used to develop efficient computational algorithms, which are then used for the processing of real-life data using Matlab.

Big Data Analysis  New Algorithms for a New Society Book

Big Data Analysis New Algorithms for a New Society


  • Author : Nathalie Japkowicz
  • Publisher : Springer
  • Release Date : 2015-12-16
  • Genre: Technology & Engineering
  • Pages : 329
  • ISBN 10 : 9783319269894

DOWNLOAD BOOK
Big Data Analysis New Algorithms for a New Society Excerpt :

This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges.

Applications in Statistical Computing Book

Applications in Statistical Computing


  • Author : Nadja Bauer
  • Publisher : Springer
  • Release Date : 2019-10-01
  • Genre: Computers
  • Pages : 340
  • ISBN 10 : 3030251462

DOWNLOAD BOOK
Applications in Statistical Computing Excerpt :

This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.

Advanced Statistical Methods for the Analysis of Large Data Sets Book

Advanced Statistical Methods for the Analysis of Large Data Sets


  • Author : Agostino Di Ciaccio
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-03-14
  • Genre: Mathematics
  • Pages : 464
  • ISBN 10 : 9783642210365

DOWNLOAD BOOK
Advanced Statistical Methods for the Analysis of Large Data Sets Excerpt :

The theme of the meeting was “Statistical Methods for the Analysis of Large Data-Sets”. In recent years there has been increasing interest in this subject; in fact a huge quantity of information is often available but standard statistical techniques are usually not well suited to managing this kind of data. The conference serves as an important meeting point for European researchers working on this topic and a number of European statistical societies participated in the organization of the event. The book includes 45 papers from a selection of the 156 papers accepted for presentation and discussed at the conference on “Advanced Statistical Methods for the Analysis of Large Data-sets.”

Computational and Statistical Methods in Intelligent Systems Book

Computational and Statistical Methods in Intelligent Systems


  • Author : Radek Silhavy
  • Publisher : Springer
  • Release Date : 2018-08-30
  • Genre: Computers
  • Pages : 386
  • ISBN 10 : 3030002101

DOWNLOAD BOOK
Computational and Statistical Methods in Intelligent Systems Excerpt :

This book presents real-world problems and pioneering research in computational statistics, mathematical modeling, artificial intelligence and software engineering in the context of intelligent systems. It gathers the peer-reviewed proceedings of the 2nd Computational Methods in Systems and Software 2018 (CoMeSySo 2018), a conference that broke down traditional barriers by being held online. The goal of the event was to provide an international forum for discussing the latest high-quality research results.

Big and Complex Data Analysis Book

Big and Complex Data Analysis


  • Author : S. Ejaz Ahmed
  • Publisher : Springer
  • Release Date : 2017-03-21
  • Genre: Mathematics
  • Pages : 386
  • ISBN 10 : 9783319415734

DOWNLOAD BOOK
Big and Complex Data Analysis Excerpt :

This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Its peer-reviewed contributions showcase recent advances in variable selection, estimation and prediction strategies for a host of useful models, as well as essential new developments in the field. The continued and rapid advancement of modern technology now allows scientists to collect data of increasingly unprecedented size and complexity. Examples include epigenomic data, genomic data, proteomic data, high-resolution image data, high-frequency financial data, functional and longitudinal data, and network data. Simultaneous variable selection and estimation is one of the key statistical problems involved in analyzing such big and complex data. The purpose of this book is to stimulate research and foster interaction between researchers in the area of high-dimensional data analysis. More concretely, its goals are to: 1) highlight and expand the breadth of existing methods in big data and high-dimensional data analysis and their potential for the advancement of both the mathematical and statistical sciences; 2) identify important directions for future research in the theory of regularization methods, in algorithmic development, and in methodologies for different application areas; and 3) facilitate collaboration between theoretical and subject-specific researchers.

Cyber Defense Mechanisms Book

Cyber Defense Mechanisms


  • Author : Gautam Kumar
  • Publisher : CRC Press
  • Release Date : 2020-09-20
  • Genre: Computers
  • Pages : 216
  • ISBN 10 : 9781000171921

DOWNLOAD BOOK
Cyber Defense Mechanisms Excerpt :

This book discusses the evolution of security and privacy issues and brings related technological tools, techniques, and solutions into one single source. The book will take readers on a journey to understanding the security issues and possible solutions involving various threats, attacks, and defense mechanisms, which include IoT, cloud computing, Big Data, lightweight cryptography for blockchain, and data-intensive techniques, and how it can be applied to various applications for general and specific use. Graduate and postgraduate students, researchers, and those working in this industry will find this book easy to understand and use for security applications and privacy issues.

The Behavioral and Social Sciences Book

The Behavioral and Social Sciences


  • Author : National Research Council
  • Publisher : National Academies Press
  • Release Date : 1988-02-01
  • Genre: Science
  • Pages : 301
  • ISBN 10 : 9780309037495

DOWNLOAD BOOK
The Behavioral and Social Sciences Excerpt :

This volume explores the scientific frontiers and leading edges of research across the fields of anthropology, economics, political science, psychology, sociology, history, business, education, geography, law, and psychiatry, as well as the newer, more specialized areas of artificial intelligence, child development, cognitive science, communications, demography, linguistics, and management and decision science. It includes recommendations concerning new resources, facilities, and programs that may be needed over the next several years to ensure rapid progress and provide a high level of returns to basic research.

Frontiers in Massive Data Analysis Book

Frontiers in Massive Data Analysis


  • Author : National Research Council
  • Publisher : National Academies Press
  • Release Date : 2013-09-03
  • Genre: Mathematics
  • Pages : 190
  • ISBN 10 : 9780309287814

DOWNLOAD BOOK
Frontiers in Massive Data Analysis Excerpt :

Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale--terabytes and petabytes--is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge--from computer science, statistics, machine learning, and application disciplines--that must be brought to bear to make useful inferences from massive data.