Big data, IoT, and machine learning : tools and applications / edited by Rashmi Agrawal, Marcin Paprzycki, Neha Gupta.
Material type:
TextSeries: Internet of everything (IoE): security and privacy paradigmPublisher: Boca Raton, FL : CRC Press, 2021Copyright date: ©2021Edition: First editionDescription: 1 online resource (xvii, 319 pages) : illustrations (some color)Content type: text Media type: computer Carrier type: online resourceISBN: 9781000098280; 1000098281; 9781000098303; 1000098303; 9780429322990; 0429322992; 9781000098297; 100009829XSubject(s): Big data | Internet of things | Machine learning | COMPUTERS / Database Management / Data MiningDDC classification: 005.7 LOC classification: QA76.9.B45 | B54 2021Online resources: Taylor & Francis | OCLC metadata license agreement Summary: 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
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
OCLC-licensed vendor bibliographic record.