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This book offers a rigorous yet approachable pathway to applying Python for mathematical problem-solving, spanning foundational concepts to advanced theoretical frameworks. It bridges the gap between abstract mathematics and computational execution, guiding readers through a logically structured, step-by-step journey. Emphasizing mathematical reasoning, symbolic computation, and real-world problem modeling, it equips readers to analyze, simulate, and visualize complex structures with clarity and efficiency. Ideal for students, researchers, and professionals in Mathematics, Data Science, AI,…mehr

Produktbeschreibung
This book offers a rigorous yet approachable pathway to applying Python for mathematical problem-solving, spanning foundational concepts to advanced theoretical frameworks. It bridges the gap between abstract mathematics and computational execution, guiding readers through a logically structured, step-by-step journey. Emphasizing mathematical reasoning, symbolic computation, and real-world problem modeling, it equips readers to analyze, simulate, and visualize complex structures with clarity and efficiency. Ideal for students, researchers, and professionals in Mathematics, Data Science, AI, Physics, and Computational Science, it cultivates both programming skill and deep mathematical intuition.
Autorenporträt
Dr. Pradeep Singh is a National Post-Doctoral Fellow and Principal Investigator at the Machine Intelligence Lab, Department of Computer Science and Engineering at the Indian Institute of Technology Roorkee (IIT) Roorkee. His research spans Geometric Deep Learning, Neuro-symbolic AI, and Dynamical Systems, funded by the Anusandhan National Research Foundation (ANRF), Department of Science and Technology, India. His research has appeared in IEEE Transactions, Biomedical Signal Processing and Control, Computers & Geosciences, Journal of Forecasting, ECAI and ACM Multimedia, contributing to the wider dialogue in AI and dynamical-systems research. He has co-authored books such as "Deep Learning Through the Prism of Tensors", "The Geometry of Intelligence: Foundations of Transformer Networks", and "Machine Learning and Artificial Intelligence". He earned his Ph.D. (2022) and Master’s degree from IIT Delhi, specializing in Symbolic Systems, and a Bachelor’s degree in Data Science from IIT Madras. Dr. Singh has received several awards, including the National Board for Higher Mathematics (NBHM) Master’s, Doctoral, and Post-Doctoral Fellowships awarded by the Department of Atomic Energy, India. In 2019, he was one of only two researchers nationwide to receive the Dr Shyama Prasad Mukherjee (SPM) Fellowship in Mathematics from CSIR, India. Dr. Balasubramanian Raman (Senior Member, IEEE) is Professor (HAG) and Head of the Department of Computer Science & Engineering at the Indian Institute of Technology (IIT) Roorkee, where he also holds a joint appointment with the Mehta Family School of Data Science & AI. He served as the iHUB Divyasampark Chair Professor from 2022 to 2025. Dr. Raman earned his Ph.D. from IIT Madras (2001). His research spanning machine learning, computer vision, image/video processing, and pattern recognition—has produced more than 250 peer-reviewed publications. He has undertaken post-doctoral and visiting appointments at Rutgers University, the University of Missouri–Columbia, Osaka Metropolitan University, Curtin University, and the University of Cyberjaya. He has also supervised several Ph.D. scholars. Dr. Raman has co-authored books such as Deep Learning Through the Prism of Tensors (Springer Nature, 2024), The Geometry of Intelligence: Foundations of Transformer Networks in Deep Learning (Springer Nature, 2025), and Artificial Intelligence and Machine Learning (2025). His honours include the DST BOYSCAST Fellowship, two IIT Roorkee Outstanding Teacher Awards, the Ramkumar Prize for Outstanding Teaching and Research, and the ICPC Coach Award, which recognised his teams’ top-50 finishes at the ACM ICPC World Finals.