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Titlebook: Data Science and Emerging Technologies; Proceedings of DaSET Yap Bee Wah,Michael W. Berry,Dhiya Al-Jumeily Conference proceedings 2023 The

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書目名稱Data Science and Emerging Technologies
副標題Proceedings of DaSET
編輯Yap Bee Wah,Michael W. Berry,Dhiya Al-Jumeily
視頻videohttp://file.papertrans.cn/264/263094/263094.mp4
概述Presents research works in the field of Information and Communication Technology.Provides original works presented at ICICTD 2022 held in Khulna, Bangladesh.Serves as a reference for researchers and p
叢書名稱Lecture Notes on Data Engineering and Communications Technologies
圖書封面Titlebook: Data Science and Emerging Technologies; Proceedings of DaSET Yap Bee Wah,Michael W. Berry,Dhiya Al-Jumeily Conference proceedings 2023 The
描述.The book presents selected papers from International Conference on Data Science and Emerging Technologies (DaSET 2022), held online at UNITAR International University, Malaysia, during December 20–21, 2022. This book aims to present current research and applications of data science and emerging technologies. The deployment of data science and emerging technology contributes to the achievement of the Sustainable Development Goals for social inclusion, environmental sustainability, and economic prosperity. Data science and emerging technologies such as artificial intelligence and blockchain are useful for various domains such as marketing, health care, finance, banking, environmental, and agriculture. ?An important grand challenge in data science is to determine how developments in computational and social-behavioral sciences can be combined to improve well-being, emergency response, sustainability, and civic engagement in a well-informed, data-driven society. ?The topics ofthis book include, but not limited to: artificial intelligence, big data technology, machine and deep learning, data mining, optimization algorithms, blockchain, Internet of Things (IoT), cloud computing, compute
出版日期Conference proceedings 2023
關(guān)鍵詞Data Science; Artificial Intelligence; Emerging Technologies; Big Data; Statistical Learning; Decision Su
版次1
doihttps://doi.org/10.1007/978-981-99-0741-0
isbn_softcover978-981-99-0743-4
isbn_ebook978-981-99-0741-0Series ISSN 2367-4512 Series E-ISSN 2367-4520
issn_series 2367-4512
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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