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BOOK EXCERPT:
This book gathers selected high-quality research papers presented at Arab Conference for Emerging Technologies 2020 organized virtually in Cairo during 21–23 June 2020. This book emphasizes the role and recent developments in the field of emerging technologies and artificial intelligence, and related technologies with a special focus on sustainable development in the Arab world. The book targets high-quality scientific research papers with applications, including theory, practical, prototypes, new ideas, case studies and surveys which cover machine learning applications in data science.
Product Details :
Genre |
: Technology & Engineering |
Author |
: Aboul Ella Hassanien |
Publisher |
: Springer Nature |
Release |
: 2021-05-27 |
File |
: 404 Pages |
ISBN-13 |
: 9789813361294 |
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BOOK EXCERPT:
This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business.Data science and big data go hand in hand and constitute a rapidly growing area of research and have attracted the attention of industry and business alike. The area itself has opened up promising new directions of fundamental and applied research and has led to interesting applications, especially those addressing the immediate need to deal with large repositories of data and building tangible, user-centric models of relationships in data. Data is the lifeblood of today’s knowledge-driven economy.Numerous data science models are oriented towards end users and along with the regular requirements for accuracy (which are present in any modeling), come the requirements for ability to process huge and varying data sets as well as robustness, interpretability, and simplicity (transparency). Computational intelligence with its underlying methodologies and tools helps address data analytics needs.The book is of interest to those researchers and practitioners involved in data science, Internet engineering, computational intelligence, management, operations research, and knowledge-based systems.
Product Details :
Genre |
: Technology & Engineering |
Author |
: Witold Pedrycz |
Publisher |
: Springer |
Release |
: 2017-03-21 |
File |
: 303 Pages |
ISBN-13 |
: 9783319534749 |
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BOOK EXCERPT:
This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.
Product Details :
Genre |
: Computers |
Author |
: John MacIntyre |
Publisher |
: Springer Nature |
Release |
: 2020-11-04 |
File |
: 887 Pages |
ISBN-13 |
: 9783030627461 |
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BOOK EXCERPT:
This book provides a comprehensive picture of fog computing technology, including of fog architectures, latency aware application management issues with real time requirements, security and privacy issues and fog analytics, in wide ranging application scenarios such as M2M device communication, smart homes, smart vehicles, augmented reality and transportation management. This book explores the research issues involved in the application of traditional shallow machine learning and deep learning techniques to big data analytics. It surveys global research advances in extending the conventional unsupervised or clustering algorithms, extending supervised and semi-supervised algorithms and association rule mining algorithms to big data Scenarios. Further it discusses the deep learning applications of big data analytics to fields of computer vision and speech processing, and describes applications such as semantic indexing and data tagging. Lastly it identifies 25 unsolved research problems and research directions in fog computing, as well as in the context of applying deep learning techniques to big data analytics, such as dimensionality reduction in high-dimensional data and improved formulation of data abstractions along with possible directions for their solutions.
Product Details :
Genre |
: Computers |
Author |
: C.S.R. Prabhu |
Publisher |
: Springer |
Release |
: 2019-01-04 |
File |
: 80 Pages |
ISBN-13 |
: 9789811332098 |
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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.
Product Details :
Genre |
: Computers |
Author |
: Sachi Nandan Mohanty |
Publisher |
: John Wiley & Sons |
Release |
: 2021-07-14 |
File |
: 528 Pages |
ISBN-13 |
: 9781119785859 |
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BOOK EXCERPT:
Prepare for Microsoft Exam 70-774–and help demonstrate your real-world mastery of performing key data science activities with Azure Machine Learning services. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the MCSA level. Focus on the expertise measured by these objectives: Prepare data for analysis in Azure Machine Learning and export from Azure Machine Learning Develop machine learning models Operationalize and manage Azure Machine Learning Services Use other services for machine learning This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are familiar with Azure data services, machine learning concepts, and common data science processes About the Exam Exam 70-774 focuses on skills and knowledge needed to prepare data for analysis with Azure Machine Learning; find key variables describing your data’s behavior; develop models and identify optimal algorithms; train, validate, deploy, manage, and consume Azure Machine Learning Models; and leverage related services and APIs. About Microsoft Certification Passing this exam as well as Exam 70-773: Analyzing Big Data with Microsoft R earns your MCSA: Machine Learning certifi¿cation, demonstrating your expertise in operationalizing Microsoft Azure machine learning and Big Data with R Server and SQL R Services. See full details at: microsoft.com/learning
Product Details :
Genre |
: Computers |
Author |
: Ginger Grant |
Publisher |
: Microsoft Press |
Release |
: 2018-03-01 |
File |
: 566 Pages |
ISBN-13 |
: 9780134849683 |
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BOOK EXCERPT:
Analyzing data sets has continued to be an invaluable application for numerous industries. By combining different algorithms, technologies, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our world for the better. The Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics is a collection of innovative research on the methods and applications of data analytics. While highlighting topics including artificial intelligence, data security, and information systems, this book is ideally designed for researchers, data analysts, data scientists, healthcare administrators, executives, managers, engineers, IT consultants, academicians, and students interested in the potential of data application technologies.
Product Details :
Genre |
: Computers |
Author |
: Patil, Bhushan |
Publisher |
: IGI Global |
Release |
: 2020-10-23 |
File |
: 583 Pages |
ISBN-13 |
: 9781799830542 |
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BOOK EXCERPT:
Modern critical infrastructures (CIs) (e.g., electricity, water, transportation, telecommunications, and others) form complex systems with a high degree of interdependencies from one CI to the others. Natural disasters (e.g., earthquakes, floods, droughts, landslides, and wildfires), humanmade disasters (e.g., sabotage and terrorism), and system faults (due to structural and equipment failures) will affect not only the directly impacted CI but all interdependent CIs. Risk assessment, therefore, has to be done over the entire system of CIs and should also include the social and personal impacts. According to a 2022 report, 80% of cities have been affected by significant climate change hazards represented by extreme heat (46%), heavy rainfall (36%), drought (35%), and floods (33%). The impacts of climate change, therefore, affect the complex system of the built environment and result in interrelated consequences at different scales ranging from single buildings to urban spaces and territorial infrastructures. Since it is not possible to reduce the severity of natural hazards, the main opportunity for lowering risk lies in reducing vulnerability and exposure. Vulnerability and exposure are related to urban development choices and practices that weaken the system’s robustness. This volume reviews recent insights from risk identification and reduction to preparedness and financial protection strategies and proposes new approaches for better CIs and built environment protection.
Product Details :
Genre |
: Technology & Engineering |
Author |
: Antonio Di Pietro |
Publisher |
: BoD – Books on Demand |
Release |
: 2024-02-14 |
File |
: 131 Pages |
ISBN-13 |
: 9781837681075 |
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BOOK EXCERPT:
The book will focus on the applications of machine learning for sustainable development. Machine learning (ML) is an emerging technique whose diffusion and adoption in various sectors (such as energy, agriculture, internet of things, infrastructure) will be of enormous benefit. The state of the art of machine learning models is most useful for forecasting and prediction of various sectors for sustainable development.
Product Details :
Genre |
: Computers |
Author |
: Kamal Kant Hiran |
Publisher |
: Walter de Gruyter GmbH & Co KG |
Release |
: 2021-07-19 |
File |
: 214 Pages |
ISBN-13 |
: 9783110702514 |
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BOOK EXCERPT:
As data is an important asset for any organization, it is essential to apply semantic technologies in data science to fulfill the need of any organization. This first volume of a two-volume handbook set provides a roadmap for new trends and future developments of data science with semantic technologies. Data Science with Semantic Technologies: New Trends and Future Developments highlights how data science enables the user to create intelligence through these technologies. In addition, this book offers the answers to various questions such as: Can semantic technologies facilitate data science? Which type of data science problems can be tackled by semantic technologies? How can data scientists benefit from these technologies? What is the role of semantic technologies in data science? What is the current progress and future of data science with semantic technologies? Which types of problems require the immediate attention of the researchers? What should be the vision 2030 for data science? This volume can serve as an important guide toward applications of data science with semantic technologies for the upcoming generation and, thus, it is a unique resource for scholars, researchers, professionals, and practitioners in this field.
Product Details :
Genre |
: Computers |
Author |
: Archana Patel |
Publisher |
: CRC Press |
Release |
: 2023-06-20 |
File |
: 293 Pages |
ISBN-13 |
: 9781000881233 |