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Big Data, IoT, and Machine Learning

2020-09-01 Computers
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Release : 2020-09-01
Genre : Computers
Kind : eBook
Book Rating : 281/5 ( reviews)

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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. This book was released on 2020-09-01. 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

Proceedings of the International Conference on Big Data, IoT, and Machine Learning

2021-12-03 Technology & Engineering
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Release : 2021-12-03
Genre : Technology & Engineering
Kind : eBook
Book Rating : 369/5 ( reviews)

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Book Synopsis Proceedings of the International Conference on Big Data, IoT, and Machine Learning by : Mohammad Shamsul Arefin

Download or read book Proceedings of the International Conference on Big Data, IoT, and Machine Learning written by Mohammad Shamsul Arefin. This book was released on 2021-12-03. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

Tech Trends in Practice

2020-04-09 Business & Economics
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Release : 2020-04-09
Genre : Business & Economics
Kind : eBook
Book Rating : 200/5 ( reviews)

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Book Synopsis Tech Trends in Practice by : Bernard Marr

Download or read book Tech Trends in Practice written by Bernard Marr. This book was released on 2020-04-09. Available in PDF, EPUB and Kindle. Book excerpt: ***BUSINESS BOOK AWARDS - FINALIST 2021*** Discover how 25 powerful technology trends are transforming 21st century businesses How will the latest technologies transform your business? Future Tech Trends in Practice will give you the knowledge of today’s most important technology trends, and how to take full advantage of them to grow your business. The book presents25 real-world technology trends along with their potential contributions to organisational success. You’ll learn how to integrate existing advancements and plan for those that are on the way. In this book, best-selling author, strategic business advisor, and respected futurist Bernard Marr explains the role of technology in providing innovative businesses solutions for companies of varying sizes and across different industries. He covers wide-ranging trends and provides an overview of how companies are using these new and emerging technologies in practice. You, too, can prepare your company for the potential and power of trending technology by examining these and other areas of innovation described in Future Tech Trends in Practice: Artificial intelligence, including machine and deep learning The Internet of Things and the rise of smart devices Self-driving cars and autonomous drones 3D printing and additive manufacturing Blockchain technology Genomics and gene editing Augmented, virtual and mixed reality When you understand the technology trends that are driving success, now and into the future, you’ll be better positioned to address and solve problems within your organisation.

Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing

2021-01-29 Computers
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Release : 2021-01-29
Genre : Computers
Kind : eBook
Book Rating : 132/5 ( reviews)

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Book Synopsis Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing by : Velayutham, Sathiyamoorthi

Download or read book Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing written by Velayutham, Sathiyamoorthi. This book was released on 2021-01-29. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning Approach for Cloud Data Analytics in IoT

2021-07-14 Computers
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Release : 2021-07-14
Genre : Computers
Kind : eBook
Book Rating : 855/5 ( reviews)

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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. This book was released on 2021-07-14. 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.

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