Deep Learning Convergence To Big Data Analytics

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Deep Learning Convergence To Big Data Analytics

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Author : Murad Khan
language : en
Publisher: Springer
Release Date : 2018-12-30

Deep Learning Convergence To Big Data Analytics written by Murad Khan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-30 with Computers categories.

This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classify this data in less processing time and space. Similarly, existing techniques and algorithms for deep learning in big data field have several advantages thanks to the two main branches of the deep learning, i.e. convolution and deep belief networks. This book offers insights into these techniques and applications based on these two types of deep learning. Further, it helps students, researchers, and newcomers understand big data analytics based on deep learning approaches. It also discusses various machine learning techniques in concatenation with the deep learning paradigm to support high-end data processing, data classifications, and real-time data processing issues. The classification and presentation are kept quite simple to help the readers and students grasp the basics concepts of various deep learning paradigms and frameworks. It mainly focuses on theory rather than the mathematical background of the deep learning concepts. The book consists of 5 chapters, beginning with an introductory explanation of big data and deep learning techniques, followed by integration of big data and deep learning techniques and lastly the future directions.

Challenges And Opportunities For The Convergence Of Iot Big Data And Cloud Computing

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Author : Velayutham, Sathiyamoorthi
language : en
Publisher: IGI Global
Release Date : 2021-01-29

Challenges And Opportunities For The Convergence Of Iot Big Data And Cloud Computing written by Velayutham, Sathiyamoorthi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-29 with Computers categories.

In today’s market, emerging technologies are continually assisting in common workplace practices as companies and organizations search for innovative ways to solve modern issues that arise. Prevalent applications including internet of things, big data, and cloud computing all have noteworthy benefits, but issues remain when separately integrating them into the professional practices. Significant research is needed on converging these systems and leveraging each of their advantages in order to find solutions to real-time problems that still exist. Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing is a pivotal reference source that provides vital research on the relation between these technologies and the impact they collectively have in solving real-world challenges. While highlighting topics such as cloud-based analytics, intelligent algorithms, and information security, this publication explores current issues that remain when attempting to implement these systems as well as the specific applications IoT, big data, and cloud computing have in various professional sectors. This book is ideally designed for academicians, researchers, developers, computer scientists, IT professionals, practitioners, scholars, students, and engineers seeking research on the integration of emerging technologies to solve modern societal issues.

Blockchain Big Data And Machine Learning

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Author : Neeraj Kumar
language : en
Publisher: CRC Press
Release Date : 2020-09-24

Blockchain Big Data And Machine Learning written by Neeraj Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-24 with Computers categories.

Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent research of security based on big data, blockchain and machine learning has been explained through actual work by practitioners and researchers, including their technical evaluation and comparison with existing technologies. The theoretical background and experimental case studies related to real-time environment are covered as well. Aimed at Senior undergraduate students, researchers and professionals in computer science and engineering and electrical engineering, this book: Converges Blockchain, Big Data and Machine learning in one volume. Connects Blockchain technologies with the data centric applications such Big data and E-Health. Easy to understand examples on how to create your own blockchain supported by case studies of blockchain in different industries. Covers big data analytics examples using R. Includes lllustrative examples in python for blockchain creation.

Data Analytics And Machine Learning

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Author : Pushpa Singh
language : en
Publisher: Springer Nature
Release Date : 2024-03-19

Data Analytics And Machine Learning written by Pushpa Singh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-19 with Computers categories.

This book presents an in-depth analysis of successful data-driven initiatives, highlighting how organizations have leveraged data to drive decision-making processes, optimize operations, and achieve remarkable outcomes. Through case studies, readers gain valuable insights and learn practical strategies for implementing data analytics, big data, and machine learning solutions in their own organizations. The book discusses the transformative power of data analytics and big data in various industries and sectors and how machine learning applications have revolutionized exploration by enabling advanced data analysis techniques for mapping, geospatial analysis, and environmental monitoring, enhancing our understanding of the world and its dynamic processes. This book explores how big data explosion, the power of analytics and machine learning revolution can bring new prospects and opportunities in the dynamic and data-rich landscape. It highlights the future research directions in data analytics, big data, and machine learning that explores the emerging trends, challenges, and opportunities in these fields by covering interdisciplinary approaches such as handling and analyzing real-time and streaming data.

Deep Learning And Neural Networks Concepts Methodologies Tools And Applications

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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2019-10-11

Deep Learning And Neural Networks Concepts Methodologies Tools And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-11 with Computers categories.

Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in various real-world applications such as computer vision, image processing, and pattern recognition. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications is a vital reference source that trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. It also explores the latest concepts, algorithms, and techniques of deep learning and data mining and analysis. Highlighting a range of topics such as natural language processing, predictive analytics, and deep neural networks, this multi-volume book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of deep learning.

Spatiotemporal Data Analytics And Modeling

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Author : John A
language : en
Publisher: Springer Nature
Release Date : 2024-04-15

Spatiotemporal Data Analytics And Modeling written by John A and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-15 with Computers categories.

With the growing advances in technology and transformation to digital services, the world is becoming more connected and more complex. Huge heterogeneous data are generated at rapid speed from various types of sensors. Augmented with artificial intelligence and machine learning and internet of things, latent relations, and new insights can be captured helping in optimizing plans and resource utilization, improving infrastructure, and enhancing quality of services. A “spatial data management system” is a way to take care of data that has something to do with space. This could include data such as maps, satellite images, and GPS data. A temporal data management system is a system designed to manage data that has a temporal component. This could include data such as weather data, financial data, and social media data. Some advanced techniques used in spatial and temporal data management systems include geospatial indexing for efficient querying and retrieval of location-based data, time-series analysis for understanding and predicting temporal patterns in datasets like weather or financial trends, machine learning algorithms for uncovering hidden patterns and correlations in large and complex datasets, and integration with Internet of Things (IoT) technologies for real-time data collection and analysis. These techniques, augmented with artificial intelligence, enable the extraction of latent relations and insights, thereby optimizing plans, improving infrastructure, and enhancing the quality of services. This book provides essential technical knowledge, best practices, and case studies on the state-of-the-art techniques of artificial intelligence and machine learning for spatiotemporal data analysis and modeling. The book is composed of several chapters written by experts in their fields and focusing on several applications including recommendation systems, big data analytics, supply chains and e-commerce, energy consumption and demand forecasting,and traffic and environmental monitoring. It can be used as academic reference at graduate level or by professionals in science and engineering related fields such as data science and engineering, big data analytics and mining, artificial intelligence, machine learning and deep learning, cloud computing, and internet of things.

Data Science And Analytics

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Author : Usha Batra
language : en
Publisher: Springer Nature
Release Date : 2020-05-27

Data Science And Analytics written by Usha Batra and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-27 with Computers categories.

This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics.

Handbook Of Research On Consumer Behavior Change And Data Analytics In The Socio Digital Era

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Author : Keikhosrokiani, Pantea
language : en
Publisher: IGI Global
Release Date : 2022-06-24

Handbook Of Research On Consumer Behavior Change And Data Analytics In The Socio Digital Era written by Keikhosrokiani, Pantea and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-24 with Business & Economics categories.

The emergence of new technologies within the industrial revolution has transformed businesses to a new socio-digital era. In this new era, businesses are concerned with collecting data on customer needs, behaviors, and preferences for driving effective customer engagement and product development, as well as for crucial decision making. However, the ever-shifting behaviors of consumers provide many challenges for businesses to pinpoint the wants and needs of their audience. The Handbook of Research on Consumer Behavior Change and Data Analytics in the Socio-Digital Era focuses on the concepts, theories, and analytical techniques to track consumer behavior change. It provides multidisciplinary research and practice focusing on social and behavioral analytics to track consumer behavior shifts and improve decision making among businesses. Covering topics such as consumer sentiment analysis, emotional intelligence, and online purchase decision making, this premier reference source is a timely resource for business executives, entrepreneurs, data analysts, marketers, advertisers, government officials, social media professionals, libraries, students and educators of higher education, researchers, and academicians.

Proceedings Of The Icsdi 2024 Volume 3

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Author : Yasser Mansour
language : en
Publisher: Springer Nature
Release Date : 2024-10-25

Proceedings Of The Icsdi 2024 Volume 3 written by Yasser Mansour and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-25 with Technology & Engineering categories.

This book offers a comprehensive overview of the latest research, innovations, and practical applications in the field of sustainability, with a focus on construction materials and their use in building and civil engineering structures. As an outcome of the 2nd International Conference on Sustainability: Developments and Innovations (ICSDI 2024), the book presents a selection of peer-reviewed papers from prominent researchers and engineers around the world. The book covers a broad range of topics, including construction and resilient infrastructure, sustainable manufacturing, industrial ecology, renewable energy, future cities, sustainable built environment design, and policies, regulations, and economics for achieving sustainable development goals. This book will serve as an essential reference for graduate students, engineers, and scientists, as well as industry professionals working in the field of sustainability. The book aligns with the scope of book series scope which aims tocontribute to progress in the construction sciences, techniques, and industries through communication between research and practice. It is also a valuable resource for practitioners and policymakers who are interested in understanding the latest technological advancements and innovations in sustainability to solve real-world problems.

Proceedings Of The 5th International Conference On Big Data Analytics For Cyber Physical System In Smart City Volume 1

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Author : Mohammed Atiquzzaman
language : en
Publisher: Springer Nature
Release Date : 2025-02-01

Proceedings Of The 5th International Conference On Big Data Analytics For Cyber Physical System In Smart City Volume 1 written by Mohammed Atiquzzaman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-01 with Computers categories.

This book gathers a selection of peer-reviewed papers presented at the 5th Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2023) conference, held in Fuyang, China, on December 28–29. The contributions, prepared by an international team of scientists and engineers, cover the latest advances and challenges made in the field of big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.