Emerging Trends in Machine Learning, Data Science, and Internet of Things (Part 2)
Language: English
Published by Bentham Science Publishers, 2026
- Softcover
- New

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- Title
- Emerging Trends in Machine Learning, Data Science, and Internet of Things (Part 2)
- Author
- Kumar, Manoj
- Publisher
- Bentham Science Publishers
- Publication year
- 2026
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798898815189
Emerging Trends in Machine Learning, Data Science, and Internet of Things Volumes 1 & 2 explores the technologies shaping the future of intelligent systems. Covering Machine Learning, Data Science, IoT, Blockchain, Cloud Computing, and Artificial Intelligence, the book focuses on designing and applying secure, data-driven solutions across healthcare, agriculture, transportation, education, cybersecurity, and digital content management.
It blends cutting-edge research with practical implementations, including AI-driven disease prediction, anomaly detection for network security, sentiment analysis, smart IoT applications, and blockchain-enabled digital authentication. The volumes highlight both theoretical foundations and real-world case studies, offering actionable insights for researchers and industry professionals alike.
Key Features:
-Comprehensive coverage of AI, ML, IoT, and Data Science applications.
-Case studies on healthcare, agriculture, cybersecurity, and digital systems.
-Practical implementations and comparative analyses of models.
-Interdisciplinary insights, including AR, blockchain, and smart systems.
-Focuses on both theory and real-world application.
It blends cutting-edge research with practical implementations, including AI-driven disease prediction, anomaly detection for network security, sentiment analysis, smart IoT applications, and blockchain-enabled digital authentication. The volumes highlight both theoretical foundations and real-world case studies, offering actionable insights for researchers and industry professionals alike.
Key Features:
-Comprehensive coverage of AI, ML, IoT, and Data Science applications.
-Case studies on healthcare, agriculture, cybersecurity, and digital systems.
-Practical implementations and comparative analyses of models.
-Interdisciplinary insights, including AR, blockchain, and smart systems.
-Focuses on both theory and real-world application.
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