Practical Graph Intelligence 1

Practical Graph Intelligence 1 is positioned at the intersection of graph theory, network science and applied computing, offering a structured pathway for understanding and implementing graph-based solutions. This book systematically develops core concepts in graph algorithms and network analysis, while emphasizing practical implementation using Python. It explores fundamental structures, traversal techniques, optimization strategies and real-world network modeling, enabling readers to translate theory into scalable applications. Through clear explanations and hands-on examples, the book supports learners in building analytical skills required for domains such as artificial intelligence (AI), data science, cybersecurity and social network analysis. Designed for students, researchers and professionals, this book bridges the gap between mathematical foundations and computational practice, fostering the development of efficient and intelligent network-driven systems.

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.