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Data Science and Emerging Technologies : Proceedings of DaSET 2024 / edited by Yap Bee Wah, Dhiya Al-Jumeily, Michael W. Berry.
Springer eBooks EBA - Intelligent Technologies and Robotics Collection 2026 Available online
View online- Format:
- Book
- Author/Creator:
- Wah, Yap Bee.
- Series:
- Lecture Notes on Data Engineering and Communications Technologies, 2367-4520 ; 257
- Language:
- English
- Subjects (All):
- Computational intelligence.
- Artificial intelligence.
- Quantitative research.
- Cooperating objects (Computer systems).
- Image processing--Digital techniques.
- Image processing.
- Computer vision.
- Computational Intelligence.
- Artificial Intelligence.
- Data Analysis and Big Data.
- Cyber-Physical Systems.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Local Subjects:
- Computational Intelligence.
- Artificial Intelligence.
- Data Analysis and Big Data.
- Cyber-Physical Systems.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Physical Description:
- 1 online resource (941 pages)
- Edition:
- 1st ed. 2026.
- Place of Publication:
- Singapore : Springer Nature Singapore : Imprint: Springer, 2026.
- Summary:
- The book presents selected papers from the Third International Conference on Data Science and Emerging Technologies (DaSET 2024), held hybrid at UNITAR International University. Malaysia, from December 11–12, 2024. 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 generative AI, artificial intelligence and blockchain are useful for various domains such as marketing, health care, education, finance, banking, environmental, and agriculture. An important grand challenge in data science is to determine how developments in generative AI, 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 of this book include, but are not limited to: generative AI, artificial intelligence, machine and deep learning, statistical learning, and health and industrial applications.
- Contents:
- Data Science and Analytics
- Machine Learning Techniques and Applications
- Healthcare and Medical AI Applications
- Cybersecurity and Awareness
- Business, Education, IoT, and the Environment.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 9789819677498
- OCLC:
- 1564372754
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