Methodologies, Frameworks, and Applications of Machine Learning

Methodologies, Frameworks, and Applications of Machine Learning

Release Date: March, 2024|Copyright: © 2024 |Pages: 296
DOI: 10.4018/979-8-3693-1062-5
ISBN13: 9798369310625|EISBN13: 9798369310632
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Description & Coverage
Description:

Technology is constantly evolving, and machine learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest machine learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making.

Academic scholars seeking to unlock the potential of machine learning in the context of Industry 5.0 and advanced IoT applications will find that the groundbreaking book, Methodologies, Frameworks, and Applications of Machine Learning, introduces an unmissable opportunity to delve into the forefront of modern research and application. This book offers a wealth of knowledge and practical insights across a wide array of topics, ranging from conceptual frameworks and methodological approaches to the application of probability theory, statistical techniques, and machine learning in domains as diverse as e-government, healthcare, cyber-physical systems, and sustainable development, this comprehensive guide equips you with the tools to navigate the complexities of Industry 5.0 and the Internet of Things (IoT).

Students, researchers, and practitioners will find that this book serves as a beacon of wisdom, guiding towards the future of machine learning and its innumerable applications. Harness the power of machine learning to address real-world challenges and transform the way we perceive and engage with the world.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Conceptual Frameworks
  • Cyber-Physical Systems
  • Data Management
  • Data-Driven Decision-Making
  • Education Applications
  • E-Government
  • Finance Applications
  • Frameworks
  • Healthcare Applications
  • Industry 5.0
  • Internet of Things
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Editor/Author Biographies
Pramod Kumar Srivastava is working as dean (student welfare) at Rajkiya Engineering College, Azamgarh (Affiliated to Dr APJ Abdul Kalam Technical University, Lucknow), India. He has a doctorate in mathematics from the University of Allahabad, Allahabad, India. He has several publications in various reputed international journals and international conferences. Dr Srivastava has also published multiple books. His research interests include wireless sensor networks, mathematical modelling, and social networks. He possesses over 15 years of teaching and research expertise, having authored over 30 publications in esteemed international journals, published more than 4 patents, edited 2 books, and provided guidance for Ph.D. candidates. He has successfully guided two PhD student and is presently guiding a few more. Excellence in learning has been his motto since he was a student and the proof of this was the gold medal awarded to him for securing the highest marks in his postgraduation. He has applied this motto in his teaching too, and being well known in his genre, he has been invited to give guest lectures at reputed institutes as well as international conferences. He has been a member of organizing committees as well as technical committees of many international conferences.
Ashok Kumar Yadav, with a B.Tech. from AKTU Lucknow, an M.Tech., and Ph.D. from JNU New Delhi, India, holds over seven years of combined teaching and research experience. Currently an assistant professor in the Department of Information Technology at Rajkiya Engineering College in Azamgarh, India. He previously served at the University of Delhi as an assistant professor (On ad-hoc). Dr. Yadav's research spans MADM, blockchain technology, machine learning, and mobility management in mobile communication. His impactful contributions include publications in esteemed journals such as Elsevier, Springer, World Scientific, and Taylor & Francis, alongside presentations at reputable international conferences. Notably, he co-authored "Mastering Disruptive Technologies" and holds Six SCIs, two Scopus publications, and six patents. Actively engaged in academia, he reviews for international journals and contributes to program committees at various conferences. He was honored with the Best paper Award in IEEE World Conference on Applied Intelligence and Computing, 2022, held during June 17–19, 2022 and International Conference on Artificial Intelligence and Smart Communication (AISC), held during January 27-29, 2023.
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