Computational and Statistical Methods for Analysing Big Data with Applications

Produk Detail:
  • Author : Shen Liu
  • Publisher : Academic Press
  • Pages : 206 pages
  • ISBN : 0081006519
  • Rating : 5/5 from 4 reviews
CLICK HERE TO GET THIS BOOK >>>Computational and Statistical Methods for Analysing Big Data with Applications

Download or Read online Computational and Statistical Methods for Analysing Big Data with Applications full in PDF, ePub and kindle. this book written by Shen Liu and published by Academic Press which was released on 20 November 2015 with total page 206 pages. We cannot guarantee that Computational and Statistical Methods for Analysing Big Data with Applications book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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 and Statistical Methods for Analysing Big Data with Applications

Computational and Statistical Methods for Analysing Big Data with Applications
  • Author : Shen Liu,James Mcgree,Zongyuan Ge,Yang Xie
  • Publisher : Academic Press
  • Release : 20 November 2015
GET THIS BOOK Computational and Statistical Methods for Analysing Big Data with Applications

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

Handbook of Big Data Analytics

Handbook of Big Data Analytics
  • Author : Wolfgang Karl Härdle,Henry Horng-Shing Lu,Xiaotong Shen
  • Publisher : Springer
  • Release : 20 July 2018
GET THIS BOOK Handbook of Big Data Analytics

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

Cyber Defense Mechanisms

Cyber Defense Mechanisms
  • Author : Gautam Kumar,Dinesh Kumar Saini,Nguyen Ha Huy Cuong
  • Publisher : CRC Press
  • Release : 20 September 2020
GET THIS BOOK Cyber Defense Mechanisms

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

Data Analysis and Applications 3

Data Analysis and Applications 3
  • Author : Andreas Makrides,Alex Karagrigoriou,Christos H. Skiadas
  • Publisher : John Wiley & Sons
  • Release : 31 March 2020
GET THIS BOOK Data Analysis and Applications 3

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

Functional Statistics and Related Fields

Functional Statistics and Related Fields
  • Author : Germán Aneiros,Enea G. Bongiorno,Ricardo Cao,Philippe Vieu
  • Publisher : Springer
  • Release : 30 June 2017
GET THIS BOOK Functional Statistics and Related Fields

This volume collects latest methodological and applied contributions on functional, high-dimensional and other complex data, related statistical models and tools as well as on operator-based statistics. It contains selected and refereed contributions presented at the Fourth International Workshop on Functional and Operatorial Statistics (IWFOS 2017) held in A Coruña, Spain, from 15 to 17 June 2017. The series of IWFOS workshops was initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008. Since then, many of the

Computational Methods for Data Analysis

Computational Methods for Data Analysis
  • Author : Yeliz Karaca,Carlo Cattani
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release : 17 December 2018
GET THIS BOOK Computational Methods for Data Analysis

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.

Statistical Data Analytics

Statistical Data Analytics
  • Author : Walter W. Piegorsch
  • Publisher : John Wiley & Sons
  • Release : 21 August 2015
GET THIS BOOK Statistical Data Analytics

Statistical Data Analytics Statistical Data Analytics Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery Applications of data mining and ‘big data’ increasingly take center stage in our modern, knowledge-driven society, supported by advances in computing power, automated data acquisition, social media development and interactive, linkable internet software. This book presents a coherent, technical introduction to modern statistical learning and analytics, starting from the core foundations of statistics and

Techniques and Environments for Big Data Analysis

Techniques and Environments for Big Data Analysis
  • Author : B. S.P. Mishra,Satchidananda Dehuri,Euiwhan Kim,Gi-Name Wang
  • Publisher : Springer
  • Release : 05 February 2016
GET THIS BOOK Techniques and Environments for Big Data Analysis

This volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role

Big Data Analytics

Big Data Analytics
  • Author : Anonim
  • Publisher : Elsevier
  • Release : 04 August 2015
GET THIS BOOK Big Data Analytics

While the term Big Data is open to varying interpretation, it is quite clear that the Volume, Velocity, and Variety (3Vs) of data have impacted every aspect of computational science and its applications. The volume of data is increasing at a phenomenal rate and a majority of it is unstructured. With big data, the volume is so large that processing it using traditional database and software techniques is difficult, if not impossible. The drivers are the ubiquitous sensors, devices, social

Big Data Analysis and Deep Learning Applications

Big Data Analysis and Deep Learning Applications
  • Author : Thi Thi Zin,Jerry Chun-Wei Lin
  • Publisher : Springer
  • Release : 06 June 2018
GET THIS BOOK Big Data Analysis and Deep Learning Applications

This book presents a compilation of selected papers from the first International Conference on Big Data Analysis and Deep Learning Applications (ICBDL 2018), and focuses on novel techniques in the fields of big data analysis, machine learning, system monitoring, image processing, conventional neural networks, communication, industrial information, and their applications. Readers will find insights to help them realize more efficient algorithms and systems used in real-life applications and contexts, making the book an essential reference guide for academic researchers, professionals, software

Applied Modeling Techniques and Data Analysis 1

Applied Modeling Techniques and Data Analysis 1
  • Author : Yannis Dimotikalis,Alex Karagrigoriou,Christina Parpoula,Christos H. Skiadas
  • Publisher : John Wiley & Sons
  • Release : 30 March 2021
GET THIS BOOK Applied Modeling Techniques and Data Analysis 1

BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on

Spatial Analysis

Spatial Analysis
  • Author : Tonny J. Oyana,Florence Margai
  • Publisher : CRC Press
  • Release : 28 August 2015
GET THIS BOOK Spatial Analysis

This book provides a concept-based problem-solving learning approach to mastering practical spatial analysis tasks. It draws from statistics, spatial statistics, visualization, and computational methods with the overall objective of supporting the growing field of geographic information science (GIS). The book introduces spatial concepts together with a series of helpful hands-on computer-based GIS exercises for studying and quantifying spatial patterns, distributions, and relationships.

Spatial Analysis Using Big Data

Spatial Analysis Using Big Data
  • Author : Yoshiki Yamagata,Hajime Seya
  • Publisher : Academic Press
  • Release : 03 November 2019
GET THIS BOOK Spatial Analysis Using Big Data

Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems. The methods represent a cluster of potentially transformational socio-economic modeling tools that allow researchers to capture real-time and high-resolution information to potentially reveal new socioeconomic dynamics within urban populations. Each method, written by leading exponents of the discipline, uses real-time urban big data to solve research problems in spatial science. Urban applications of these methods

Big Data Analytics

Big Data Analytics
  • Author : Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao
  • Publisher : Springer
  • Release : 12 October 2016
GET THIS BOOK Big Data Analytics

This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big

Big Data Analytics in Genomics

Big Data Analytics in Genomics
  • Author : Ka-Chun Wong
  • Publisher : Springer
  • Release : 24 October 2016
GET THIS BOOK Big Data Analytics in Genomics

This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace. To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed