Applications of Machine Learning in Big-Data Analytics and Cloud Computing
Applications of Machine Learning in Big-Data Analytics and Cloud Computing

Author: Subhendu Kumar Pani

Publisher: CRC Press

Published: 2022-09-01

Total Pages: 346

ISBN-13: 1000793559

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Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

Applications of Big Data in Large- and Small-Scale Systems
Applications of Big Data in Large- and Small-Scale Systems

Author: Goundar, Sam

Publisher: IGI Global

Published: 2021-01-15

Total Pages: 377

ISBN-13: 1799866750

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With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.

Security and Privacy for Big Data, Cloud Computing and Applications
Security and Privacy for Big Data, Cloud Computing and Applications

Author: Wei Ren

Publisher: Computing and Networks

Published: 2019-09

Total Pages: 329

ISBN-13: 1785617478

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This book examines various topics and approaches related to the security and privacy in big data and cloud computing, where authors share their expertise in their respective chapters on a broad range of security and privacy challenges and state of the art solutions.

Software Architecture for Big Data and the Cloud
Software Architecture for Big Data and the Cloud

Author: Ivan Mistrik

Publisher: Morgan Kaufmann

Published: 2017-06-12

Total Pages: 472

ISBN-13: 0128093382

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Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors. Discusses systematic and disciplined approaches to building software architectures for cloud and big data with state-of-the-art methods and techniques Presents case studies involving enterprise, business, and government service deployment of big data applications Shares guidance on theory, frameworks, methodologies, and architecture for cloud and big data

Disruptive Technologies for Big Data and Cloud Applications
Disruptive Technologies for Big Data and Cloud Applications

Author: J. Dinesh Peter

Publisher: Springer Nature

Published: 2022-08-01

Total Pages: 880

ISBN-13: 9811921776

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This book provides a written record of the synergy that already exists among the research communities and represents a solid framework in the advancement of big data and cloud computing disciplines from which new interaction will result in the future. This book is a compendium of the International Conference on Big Data and Cloud Computing (ICBDCC 2021). It includes recent advances in big data analytics, cloud computing, the Internet of nano things, cloud security, data analytics in the cloud, smart cities and grids, etc. This book primarily focuses on the application of knowledge that promotes ideas for solving the problems of society through cutting-edge technologies. The articles featured in this book provide novel ideas that contribute to the growth of world-class research and development. The contents of this book are of interest to researchers and professionals alike.

Big-Data Analytics and Cloud Computing
Big-Data Analytics and Cloud Computing

Author: Marcello Trovati

Publisher: Springer

Published: 2016-01-12

Total Pages: 178

ISBN-13: 3319253131

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This book reviews the theoretical concepts, leading-edge techniques and practical tools involved in the latest multi-disciplinary approaches addressing the challenges of big data. Illuminating perspectives from both academia and industry are presented by an international selection of experts in big data science. Topics and features: describes the innovative advances in theoretical aspects of big data, predictive analytics and cloud-based architectures; examines the applications and implementations that utilize big data in cloud architectures; surveys the state of the art in architectural approaches to the provision of cloud-based big data analytics functions; identifies potential research directions and technologies to facilitate the realization of emerging business models through big data approaches; provides relevant theoretical frameworks, empirical research findings, and numerous case studies; discusses real-world applications of algorithms and techniques to address the challenges of big datasets.

Guide to Big Data Applications
Guide to Big Data Applications

Author: S. Srinivasan

Publisher: Springer

Published: 2017-05-25

Total Pages: 567

ISBN-13: 3319538179

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This handbook brings together a variety of approaches to the uses of big data in multiple fields, primarily science, medicine, and business. This single resource features contributions from researchers around the world from a variety of fields, where they share their findings and experience. This book is intended to help spur further innovation in big data. The research is presented in a way that allows readers, regardless of their field of study, to learn from how applications have proven successful and how similar applications could be used in their own field. Contributions stem from researchers in fields such as physics, biology, energy, healthcare, and business. The contributors also discuss important topics such as fraud detection, privacy implications, legal perspectives, and ethical handling of big data.

Cloud Computing for Geospatial Big Data Analytics
Cloud Computing for Geospatial Big Data Analytics

Author: Himansu Das

Publisher: Springer

Published: 2018-12-11

Total Pages: 289

ISBN-13: 3030033597

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This book introduces the latest research findings in cloud, edge, fog, and mist computing and their applications in various fields using geospatial data. It solves a number of problems of cloud computing and big data, such as scheduling, security issues using different techniques, which researchers from industry and academia have been attempting to solve in virtual environments. Some of these problems are of an intractable nature and so efficient technologies like fog, edge and mist computing play an important role in addressing these issues. By exploring emerging advances in cloud computing and big data analytics and their engineering applications, the book enables researchers to understand the mechanisms needed to implement cloud, edge, fog, and mist computing in their own endeavours, and motivates them to examine their own research findings and developments.

Data Intensive Computing Applications for Big Data
Data Intensive Computing Applications for Big Data

Author: M. Mittal

Publisher: IOS Press

Published: 2018-01-31

Total Pages: 618

ISBN-13: 1614998140

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The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.

Big Data on Real-World Applications
Big Data on Real-World Applications

Author: Sebastian Ventura Soto

Publisher: BoD – Books on Demand

Published: 2016-07-20

Total Pages: 126

ISBN-13: 9535124897

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As technology advances, high volumes of valuable data are generated day by day in modern organizations. The management of such huge volumes of data has become a priority in these organizations, requiring new techniques for data management and data analysis in Big Data environments. These environments encompass many different fields including medicine, education data, and recommender systems. The aim of this book is to provide the reader with a variety of fields and systems where the analysis and management of Big Data are essential. This book describes the importance of the Big Data era and how existing information systems are required to be adapted to face up the problems derived from the management of massive datasets.