Applications Of Machine Learning In Big Data Analytics And Cloud Computing

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

Author : Subhendu Kumar Pani
Publisher : CRC Press
ISBN 13 : 1000793559
Total Pages : 346 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Applications of Machine Learning in Big-Data Analytics and Cloud Computing by : Subhendu Kumar Pani

Download or read book Applications of Machine Learning in Big-Data Analytics and Cloud Computing written by Subhendu Kumar Pani and published by CRC Press. This book was released on 2022-09-01 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Advanced Deep Learning Applications in Big Data Analytics

Author : Bouarara, Hadj Ahmed
Publisher : IGI Global
ISBN 13 : 1799827933
Total Pages : 351 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Advanced Deep Learning Applications in Big Data Analytics by : Bouarara, Hadj Ahmed

Download or read book Advanced Deep Learning Applications in Big Data Analytics written by Bouarara, Hadj Ahmed and published by IGI Global. This book was released on 2020-10-16 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.

Big Data, IoT, and Machine Learning

Author : Rashmi Agrawal
Publisher : CRC Press
ISBN 13 : 1000098281
Total Pages : 319 pages
Book Rating : 4.0/5 ( download)

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Book Synopsis Big Data, IoT, and Machine Learning by : Rashmi Agrawal

Download or read book Big Data, IoT, and Machine Learning written by Rashmi Agrawal and published by CRC Press. This book was released on 2020-09-01 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools. This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them. Features Addresses the complete data science technologies workflow Explores basic and high-level concepts and services as a manual for those in the industry and at the same time can help beginners to understand both basic and advanced aspects of machine learning Covers data processing and security solutions in IoT and Big Data applications Offers adaptive, robust, scalable and reliable applications to develop solutions for day-to-day problems Presents security issues and data migration techniques of NoSQL databases

Cloud Computing for Machine Learning and Cognitive Applications

Author : Kai Hwang
Publisher : MIT Press
ISBN 13 : 026203641X
Total Pages : 626 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Cloud Computing for Machine Learning and Cognitive Applications by : Kai Hwang

Download or read book Cloud Computing for Machine Learning and Cognitive Applications written by Kai Hwang and published by MIT Press. This book was released on 2017-06-16 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first textbook to teach students how to build data analytic solutions on large data sets using cloud-based technologies. This is the first textbook to teach students how to build data analytic solutions on large data sets (specifically in Internet of Things applications) using cloud-based technologies for data storage, transmission and mashup, and AI techniques to analyze this data. This textbook is designed to train college students to master modern cloud computing systems in operating principles, architecture design, machine learning algorithms, programming models and software tools for big data mining, analytics, and cognitive applications. The book will be suitable for use in one-semester computer science or electrical engineering courses on cloud computing, machine learning, cloud programming, cognitive computing, or big data science. The book will also be very useful as a reference for professionals who want to work in cloud computing and data science. Cloud and Cognitive Computing begins with two introductory chapters on fundamentals of cloud computing, data science, and adaptive computing that lay the foundation for the rest of the book. Subsequent chapters cover topics including cloud architecture, mashup services, virtual machines, Docker containers, mobile clouds, IoT and AI, inter-cloud mashups, and cloud performance and benchmarks, with a focus on Google's Brain Project, DeepMind, and X-Lab programs, IBKai HwangM SyNapse, Bluemix programs, cognitive initiatives, and neurocomputers. The book then covers machine learning algorithms and cloud programming software tools and application development, applying the tools in machine learning, social media, deep learning, and cognitive applications. All cloud systems are illustrated with big data and cognitive application examples.

Big-Data Analytics for Cloud, IoT and Cognitive Computing

Author : Kai Hwang
Publisher : John Wiley & Sons
ISBN 13 : 1119247292
Total Pages : 432 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Big-Data Analytics for Cloud, IoT and Cognitive Computing by : Kai Hwang

Download or read book Big-Data Analytics for Cloud, IoT and Cognitive Computing written by Kai Hwang and published by John Wiley & Sons. This book was released on 2017-03-17 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologies Covers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programs Offers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologies Fully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning Features a companion website with an instructor manual and PowerPoint slides www.wiley.com/go/hwangIOT Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource.

Cognitive Computing and Big Data Analytics

Author : Judith S. Hurwitz
Publisher : John Wiley & Sons
ISBN 13 : 1118896637
Total Pages : 288 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Cognitive Computing and Big Data Analytics by : Judith S. Hurwitz

Download or read book Cognitive Computing and Big Data Analytics written by Judith S. Hurwitz and published by John Wiley & Sons. This book was released on 2015-02-12 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to learning technologies that unlock the value in big data Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data. This book helps technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming. Detailed case examples from the financial, healthcare, and manufacturing walk readers step-by-step through the design and testing of cognitive systems, and expert perspectives from organizations such as Cleveland Clinic, Memorial Sloan-Kettering, as well as commercial vendors that are creating solutions. These organizations provide insight into the real-world implementation of cognitive computing systems. The IBM Watson cognitive computing platform is described in a detailed chapter because of its significance in helping to define this emerging market. In addition, the book includes implementations of emerging projects from Qualcomm, Hitachi, Google and Amazon. Today's cognitive computing solutions build on established concepts from artificial intelligence, natural language processing, ontologies, and leverage advances in big data management and analytics. They foreshadow an intelligent infrastructure that enables a new generation of customer and context-aware smart applications in all industries. Cognitive Computing is a comprehensive guide to the subject, providing both the theoretical and practical guidance technologists need. Discover how cognitive computing evolved from promise to reality Learn the elements that make up a cognitive computing system Understand the groundbreaking hardware and software technologies behind cognitive computing Learn to evaluate your own application portfolio to find the best candidates for pilot projects Leverage cognitive computing capabilities to transform the organization Cognitive systems are rightly being hailed as the new era of computing. Learn how these technologies enable emerging firms to compete with entrenched giants, and forward-thinking established firms to disrupt their industries. Professionals who currently work with big data and analytics will see how cognitive computing builds on their foundation, and creates new opportunities. Cognitive Computing provides complete guidance to this new level of human-machine interaction.

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

Author : Goundar, Sam
Publisher : IGI Global
ISBN 13 : 1799866750
Total Pages : 377 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Applications of Big Data in Large- and Small-Scale Systems by : Goundar, Sam

Download or read book Applications of Big Data in Large- and Small-Scale Systems written by Goundar, Sam and published by IGI Global. This book was released on 2021-01-15 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Intelligence, Big Data Analytics, and IoT in Image Processing

Author : Ashok Kumar
Publisher : John Wiley & Sons
ISBN 13 : 1119865492
Total Pages : 516 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Machine Intelligence, Big Data Analytics, and IoT in Image Processing by : Ashok Kumar

Download or read book Machine Intelligence, Big Data Analytics, and IoT in Image Processing written by Ashok Kumar and published by John Wiley & Sons. This book was released on 2023-02-14 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: MACHINE INTELLIGENCE, BIG DATA ANALYTICS, AND IoT IN IMAGE PROCESSING Discusses both theoretical and practical aspects of how to harness advanced technologies to develop practical applications such as drone-based surveillance, smart transportation, healthcare, farming solutions, and robotics used in automation. The concepts of machine intelligence, big data analytics, and the Internet of Things (IoT) continue to improve our lives through various cutting-edge applications such as disease detection in real-time, crop yield prediction, smart parking, and so forth. The transformative effects of these technologies are life-changing because they play an important role in demystifying smart healthcare, plant pathology, and smart city/village planning, design and development. This book presents a cross-disciplinary perspective on the practical applications of machine intelligence, big data analytics, and IoT by compiling cutting-edge research and insights from researchers, academicians, and practitioners worldwide. It identifies and discusses various advanced technologies, such as artificial intelligence, machine learning, IoT, image processing, network security, cloud computing, and sensors, to provide effective solutions to the lifestyle challenges faced by humankind. Machine Intelligence, Big Data Analytics, and IoT in Image Processing is a significant addition to the body of knowledge on practical applications emerging from machine intelligence, big data analytics, and IoT. The chapters deal with specific areas of applications of these technologies. This deliberate choice of covering a diversity of fields was to emphasize the applications of these technologies in almost every contemporary aspect of real life to assist working in different sectors by understanding and exploiting the strategic opportunities offered by these technologies. Audience The book will be of interest to a range of researchers and scientists in artificial intelligence who work on practical applications using machine learning, big data analytics, natural language processing, pattern recognition, and IoT by analyzing images. Software developers, industry specialists, and policymakers in medicine, agriculture, smart cities development, transportation, etc. will find this book exceedingly useful.

Machine Learning Approach for Cloud Data Analytics in IoT

Author : Sachi Nandan Mohanty
Publisher : John Wiley & Sons
ISBN 13 : 1119785855
Total Pages : 528 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Machine Learning Approach for Cloud Data Analytics in IoT by : Sachi Nandan Mohanty

Download or read book Machine Learning Approach for Cloud Data Analytics in IoT written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2021-07-14 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.

Machine Learning

Author : Hamed Farhadi
Publisher : BoD – Books on Demand
ISBN 13 : 1789237521
Total Pages : 231 pages
Book Rating : 4.7/5 (892 download)

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Book Synopsis Machine Learning by : Hamed Farhadi

Download or read book Machine Learning written by Hamed Farhadi and published by BoD – Books on Demand. This book was released on 2018-09-19 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume of data that is generated, stored, and communicated across different industrial sections, business units, and scientific research communities has been rapidly expanding. The recent developments in cellular telecommunications and distributed/parallel computation technology have enabled real-time collection and processing of the generated data across different sections. On the one hand, the internet of things (IoT) enabled by cellular telecommunication industry connects various types of sensors that can collect heterogeneous data. On the other hand, the recent advances in computational capabilities such as parallel processing in graphical processing units (GPUs) and distributed processing over cloud computing clusters enabled the processing of a vast amount of data. There has been a vital need to discover important patterns and infer trends from a large volume of data (so-called Big Data) to empower data-driven decision-making processes. Tools and techniques have been developed in machine learning to draw insightful conclusions from available data in a structured and automated fashion. Machine learning algorithms are based on concepts and tools developed in several fields including statistics, artificial intelligence, information theory, cognitive science, and control theory. The recent advances in machine learning have had a broad range of applications in different scientific disciplines. This book covers recent advances of machine learning techniques in a broad range of applications in smart cities, automated industry, and emerging businesses.

Advances in Machine Learning for Big Data Analysis

Author : Satchidananda Dehuri
Publisher : Springer Nature
ISBN 13 : 981168930X
Total Pages : 254 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Advances in Machine Learning for Big Data Analysis by : Satchidananda Dehuri

Download or read book Advances in Machine Learning for Big Data Analysis written by Satchidananda Dehuri and published by Springer Nature. This book was released on 2022-02-24 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems. In this book, various advancements of machine learning algorithms to extract data-driven decisions from big data in diverse domains such as the banking sector, healthcare, social media, and video surveillance are presented in several chapters. Each of them has separate functionalities, which can be leveraged to solve a specific set of big data applications. This book is a potential resource for various advances in the field of machine learning and data science to solve big data problems with many objectives. It has been observed from the literature that several works have been focused on the advancement of machine learning in various fields like biomedical, stock prediction, sentiment analysis, etc. However, limited discussions have been carried out on application of advanced machine learning techniques in solving big data problems.

Machine Learning and Data Analytics for Solving Business Problems

Author : Bader Alyoubi
Publisher : Springer
ISBN 13 : 9783031184857
Total Pages : 0 pages
Book Rating : 4.1/5 (848 download)

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Book Synopsis Machine Learning and Data Analytics for Solving Business Problems by : Bader Alyoubi

Download or read book Machine Learning and Data Analytics for Solving Business Problems written by Bader Alyoubi and published by Springer. This book was released on 2023-12-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods – such as blockchain, big data, artificial intelligence, and cloud computing – so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems.

Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges

Author : Aboul Ella Hassanien
Publisher : Springer Nature
ISBN 13 : 303059338X
Total Pages : 648 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges by : Aboul Ella Hassanien

Download or read book Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2020-12-14 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.

Advanced Analytics and Deep Learning Models

Author : Archana Mire
Publisher : John Wiley & Sons
ISBN 13 : 111979241X
Total Pages : 436 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Advanced Analytics and Deep Learning Models by : Archana Mire

Download or read book Advanced Analytics and Deep Learning Models written by Archana Mire and published by John Wiley & Sons. This book was released on 2022-05-03 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Analytics and Deep Learning Models The book provides readers with an in-depth understanding of concepts and technologies related to the importance of analytics and deep learning in many useful real-world applications such as e-healthcare, transportation, agriculture, stock market, etc. Advanced analytics is a mixture of machine learning, artificial intelligence, graphs, text mining, data mining, semantic analysis. It is an approach to data analysis. Beyond the traditional business intelligence, it is a semi and autonomous analysis of data by using different techniques and tools. However, deep learning and data analysis both are high centers of data science. Almost all the private and public organizations collect heavy amounts of data, i.e., domain-specific data. Many small/large companies are exploring large amounts of data for existing and future technology. Deep learning is also exploring large amounts of unsupervised data making it beneficial and effective for big data. Deep learning can be used to deal with all kinds of problems and challenges that include collecting unlabeled and uncategorized raw data, extracting complex patterns from a large amount of data, retrieving fast information, tagging data, etc. This book contains 16 chapters on artificial intelligence, machine learning, deep learning, and their uses in many useful sectors like stock market prediction, a recommendation system for better service selection, e-healthcare, telemedicine, transportation. There are also chapters on innovations and future opportunities with fog computing/cloud computing and artificial intelligence. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in healthcare, telemedicine, transportation, and the financial sector. The book will also be a great source for software engineers and advanced students who are beginners in the field of advanced analytics in deep learning.

Big-Data Analytics and Cloud Computing

Author : Marcello Trovati
Publisher : Springer
ISBN 13 : 3319253131
Total Pages : 169 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Big-Data Analytics and Cloud Computing by : Marcello Trovati

Download or read book Big-Data Analytics and Cloud Computing written by Marcello Trovati and published by Springer. This book was released on 2016-01-12 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Convergence of Cloud with AI for Big Data Analytics

Author : Danda B. Rawat
Publisher : John Wiley & Sons
ISBN 13 : 1119905214
Total Pages : 452 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Convergence of Cloud with AI for Big Data Analytics by : Danda B. Rawat

Download or read book Convergence of Cloud with AI for Big Data Analytics written by Danda B. Rawat and published by John Wiley & Sons. This book was released on 2023-02-13 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: CONVERGENCE of CLOUD with AI for BIG DATA ANALYTICS This book covers the foundations and applications of cloud computing, AI, and Big Data and analyses their convergence for improved development and services. The 17 chapters of the book masterfully and comprehensively cover the intertwining concepts of artificial intelligence, cloud computing, and big data, all of which have recently emerged as the next-generation paradigms. There has been rigorous growth in their applications and the hybrid blend of AI Cloud and IoT (Ambient-intelligence technology) also relies on input from wireless devices. Despite the multitude of applications and advancements, there are still some limitations and challenges to overcome, such as security, latency, energy consumption, service allocation, healthcare services, network lifetime, etc. Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation details all these technologies and how they are related to state-of-the-art applications, and provides a comprehensive overview for readers interested in advanced technologies, identifying the challenges, proposed solutions, as well as how to enhance the framework. Audience Researchers and post-graduate students in computing as well as engineers and practitioners in software engineering, electrical engineers, data analysts, and cyber security professionals.

Integration of Cloud Computing with Internet of Things

Author : Monika Mangla
Publisher : John Wiley & Sons
ISBN 13 : 111976887X
Total Pages : 386 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Integration of Cloud Computing with Internet of Things by : Monika Mangla

Download or read book Integration of Cloud Computing with Internet of Things written by Monika Mangla and published by John Wiley & Sons. This book was released on 2021-04-13 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book aims to integrate the aspects of IoT, Cloud computing and data analytics from diversified perspectives. The book also plans to discuss the recent research trends and advanced topics in the field which will be of interest to academicians and researchers working in this area. Thus, the book intends to help its readers to understand and explore the spectrum of applications of IoT, cloud computing and data analytics. Here, it is also worth mentioning that the book is believed to draw attention on the applications of said technology in various disciplines in order to obtain enhanced understanding of the readers. Also, this book focuses on the researches and challenges in the domain of IoT, Cloud computing and Data analytics from perspectives of various stakeholders.