Practical Graph Intelligence 2 delivers a comprehensive and application driven exploration of graph-based methods for understanding complex, interconnected data.
This book bridges theory and practice by presenting advanced techniques in graph theory, graph neural networks and network analytics, with a strong focus on real-world implementation. It addresses critical challenges such as scalability, interpretability and dynamic data handling while showcasing applications across healthcare, cybersecurity, social networks and smart systems.
Designed for researchers, practitioners and advanced students, this book highlights emerging trends and practical frameworks that enable efficient, data-driven decision-making. By integrating cutting-edge research with hands-on perspectives, it serves as a valuable resource for developing robust and intelligent graph-based solutions in today’s data intensive environments.
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Pramod Singh Rathore is an Assistant Professor at Manipal University Jaipur, India. His expertise includes NS2, networks, data mining and DBMS.
Abhishek Kumar is a Professor at Chandigarh University, India. His expertise includes AI, renewable energy and image processing.
Priya Batta is an Associate Professor at Amity School of Engineering and Technology, Amity University Punjab, Mohali, India. Her expertise includes AI, blockchain and IoT.
Inam Ul Haq is an Assistant Professor at the School of Engineering and Technology (SET), CGC University Mohali, Punjab, India. His expertise includes AI, machine learning and quantum computing.
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Hardcover. Condición: new. Hardcover. Practical Graph Intelligence 2 delivers a comprehensive and application driven exploration of graph-based methods for understanding complex, interconnected data. This book bridges theory and practice by presenting advanced techniques in graph theory, graph neural networks and network analytics, with a strong focus on real-world implementation. It addresses critical challenges such as scalability, interpretability and dynamic data handling while showcasing applications across healthcare, cybersecurity, social networks and smart systems. Designed for researchers, practitioners and advanced students, this book highlights emerging trends and practical frameworks that enable efficient, data-driven decision-making. By integrating cutting-edge research with hands-on perspectives, it serves as a valuable resource for developing robust and intelligent graph-based solutions in todays data intensive environments. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9781836691624
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Hardcover. Condición: new. Hardcover. Practical Graph Intelligence 2 delivers a comprehensive and application driven exploration of graph-based methods for understanding complex, interconnected data. This book bridges theory and practice by presenting advanced techniques in graph theory, graph neural networks and network analytics, with a strong focus on real-world implementation. It addresses critical challenges such as scalability, interpretability and dynamic data handling while showcasing applications across healthcare, cybersecurity, social networks and smart systems. Designed for researchers, practitioners and advanced students, this book highlights emerging trends and practical frameworks that enable efficient, data-driven decision-making. By integrating cutting-edge research with hands-on perspectives, it serves as a valuable resource for developing robust and intelligent graph-based solutions in todays data intensive environments. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9781836691624
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Buch. Condición: Neu. Neuware - Practical Graph Intelligence 2 delivers a comprehensive and application driven exploration of graph-based methods for understanding complex, interconnected data. This book bridges theory and practice by presenting advanced techniques in graph theory, graph neural networks and network analytics, with a strong focus on real-world implementation. It addresses critical challenges such as scalability, interpretability and dynamic data handling while showcasing applications across healthcare, cybersecurity, social networks and smart systems. Designed for researchers, practitioners and advanced students, this book highlights emerging trends and practical frameworks that enable efficient, data-driven decision-making. By integrating cutting-edge research with hands-on perspectives, it serves as a valuable resource for developing robust and intelligent graph-based solutions in today's data intensive environments. Nº de ref. del artículo: 9781836691624
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