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Building Business Models with Machine Learning (Advances in Systems Analysis, Software Engineering, and High Performance Computing) - Softcover

 
9798369350973: Building Business Models with Machine Learning (Advances in Systems Analysis, Software Engineering, and High Performance Computing)

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Organizations worldwide grapple with the complexities of incorporating machine learning into their business models while ensuring sustainability. This book offers practical insights and strategies for integrating machine learning into organizational plans.

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About the Authors

Ambika N. is an MCA, MPhil, and Ph.D. in computer science. She completed her Ph.D. from Bharathiar university in the year 2015. She has 18 years of teaching experience and works for St.Francis College, Bangalore. She has guided BCA, MCA, and M.Tech students in their projects. Her expertise includes wireless sensor networks, the Internet of things, and cybersecurity. She gives guest lectures on her expertise. She reviews books, conferences (national/international), encyclopedias, and journals. She is advisory committee member of some conferences. She has many publications in National & international conferences, international books, national and international journals, and encyclopedias. She has some patent publications (National) and has received 5 copyrights in the computer science division.

Vishal Jain is presently working as an Associate Professor at Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, U. P. India. Before that, he has worked for several years as an Associate Professor at Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM), New Delhi. He has more than 14 years of experience in the academics. He obtained Ph.D (CSE), M.Tech (CSE), MBA (HR), MCA, MCP and CCNA. He has authored more than 90 research papers in reputed conferences and journals, including Web of Science and Scopus. He has authored and edited more than 30 books with various reputed publishers, including Elsevier, Springer, Apple Academic Press, CRC, Taylor and Francis Group, Scrivener, Wiley, Emerald, NOVA Science and IGI-Global. His research areas include information retrieval, semantic web, ontology engineering, data mining, ad hoc networks, and sensor networks. He received a Young Active Member Award for the year 2012–13 from the Computer Society of India, Best Faculty Award for the year 2017 and Best Researcher Award for the year 2019 from BVICAM, New Delhi.

Dac-Nhuong Le (Lê Đắc Nhường) has an MSc and PhD in computer science from Vietnam National University, Vietnam in 2009 and 2015, respectively. He is an Associate Professor of Computer Science and Dean of the Faculty of Information Technology at Haiphong University, Vietnam. He has 20+ years of academic teaching experience in computer science. He has many publications in reputed international conferences, journals, and book chapters (Indexed by SCIE, SSCI, ESCI, Scopus). His research areas include intelligence computing, multi-objective optimization, network security, cloud computing, virtual reality/augmented reality, and IoT. Recently, he has served on the technical program committee, conducted technical reviews, and acted as a track chair for international conferences under the Springer-ASIC/LNAI/CISC Series. He also serves on the editorial board of international journals and has edited/authored 30+ computer science books published by Springer, Wiley, CRC Press, IET, IGI Global, and Bentham Publishers.

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Published by Engineering Science Reference, 2024
ISBN 13: 9798369350973
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Paperback. Condition: new. Paperback. Organizations worldwide grapple with the complexities of incorporating machine learning into their business models while ensuring sustainability. Decision-makers, data scientists, and business executives face the challenge of navigating this terrain to drive innovation and maintain a competitive edge. Building Business Models with Machine Learning provides a comprehensive solution, offering practical insights and strategies for integrating machine learning into organizational plans. By bridging the gap between theory and practice, we empower readers to leverage machine learning effectively, enabling them to develop resilient and flexible business models. The book serves as a vital resource for those seeking to understand the nuances of sustainable management in a volatile, uncertain, complex, and ambiguous (VUCA) world. It addresses key challenges such as irrational decision-making and the need for adaptive systems in modern business environments. Through a combination of theoretical frameworks and empirical research findings, our book equips readers with the knowledge and tools needed to navigate these challenges successfully. Whether you are a seasoned professional, a postgraduate MBA program, or a managerial sciences student, this book offers invaluable insights that will significantly enhance your understanding and application of machine learning in business models. Building Business Models with Machine Learning focuses on problem-solving and practical application. It provides a roadmap for incorporating machine learning into organizational strategies and covers a wide range of topics, including sustainability in business models, machine learning in healthcare, and online fraud detection. By offering a thorough manual for integrating learning into organizational plans, this book enables readers to develop data-driven, adaptable business models essential for success in today's dynamic business landscape. Organizations worldwide grapple with the complexities of incorporating machine learning into their business models while ensuring sustainability. This book offers practical insights and strategies for integrating machine learning into organizational plans. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798369350973

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Ambika N.
Published by IGI Global, Hershey, PA, 2024
ISBN 13: 9798369350973
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Paperback. Condition: new. Paperback. Organizations worldwide grapple with the complexities of incorporating machine learning into their business models while ensuring sustainability. Decision-makers, data scientists, and business executives face the challenge of navigating this terrain to drive innovation and maintain a competitive edge. Building Business Models with Machine Learning provides a comprehensive solution, offering practical insights and strategies for integrating machine learning into organizational plans. By bridging the gap between theory and practice, we empower readers to leverage machine learning effectively, enabling them to develop resilient and flexible business models. The book serves as a vital resource for those seeking to understand the nuances of sustainable management in a volatile, uncertain, complex, and ambiguous (VUCA) world. It addresses key challenges such as irrational decision-making and the need for adaptive systems in modern business environments. Through a combination of theoretical frameworks and empirical research findings, our book equips readers with the knowledge and tools needed to navigate these challenges successfully. Whether you are a seasoned professional, a postgraduate MBA program, or a managerial sciences student, this book offers invaluable insights that will significantly enhance your understanding and application of machine learning in business models. Building Business Models with Machine Learning focuses on problem-solving and practical application. It provides a roadmap for incorporating machine learning into organizational strategies and covers a wide range of topics, including sustainability in business models, machine learning in healthcare, and online fraud detection. By offering a thorough manual for integrating learning into organizational plans, this book enables readers to develop data-driven, adaptable business models essential for success in today's dynamic business landscape. Organizations worldwide grapple with the complexities of incorporating machine learning into their business models while ensuring sustainability. This book offers practical insights and strategies for integrating machine learning into organizational plans. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798369350973

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Ambika N.
Published by IGI Global, Hershey, PA, 2024
ISBN 13: 9798369350973
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Paperback. Condition: new. Paperback. Organizations worldwide grapple with the complexities of incorporating machine learning into their business models while ensuring sustainability. Decision-makers, data scientists, and business executives face the challenge of navigating this terrain to drive innovation and maintain a competitive edge. Building Business Models with Machine Learning provides a comprehensive solution, offering practical insights and strategies for integrating machine learning into organizational plans. By bridging the gap between theory and practice, we empower readers to leverage machine learning effectively, enabling them to develop resilient and flexible business models. The book serves as a vital resource for those seeking to understand the nuances of sustainable management in a volatile, uncertain, complex, and ambiguous (VUCA) world. It addresses key challenges such as irrational decision-making and the need for adaptive systems in modern business environments. Through a combination of theoretical frameworks and empirical research findings, our book equips readers with the knowledge and tools needed to navigate these challenges successfully. Whether you are a seasoned professional, a postgraduate MBA program, or a managerial sciences student, this book offers invaluable insights that will significantly enhance your understanding and application of machine learning in business models. Building Business Models with Machine Learning focuses on problem-solving and practical application. It provides a roadmap for incorporating machine learning into organizational strategies and covers a wide range of topics, including sustainability in business models, machine learning in healthcare, and online fraud detection. By offering a thorough manual for integrating learning into organizational plans, this book enables readers to develop data-driven, adaptable business models essential for success in today's dynamic business landscape. Organizations worldwide grapple with the complexities of incorporating machine learning into their business models while ensuring sustainability. This book offers practical insights and strategies for integrating machine learning into organizational plans. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9798369350973

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