E-Book, Englisch, 619 Seiten
Kumar / Juárez Ramírez / Quezada Mathematical Methods in Artificial Intelligence
1. Auflage 2026
ISBN: 978-3-11-222132-7
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 6 - ePub Watermark
Intelligent Systems
E-Book, Englisch, 619 Seiten
Reihe: De Gruyter Proceedings in Mathematics
ISBN: 978-3-11-222132-7
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 6 - ePub Watermark
In today’s data-driven era, the convergence of mathematics, computing, artificial intelligence, and blockchain is emerging as a significant area at the intersection of applied mathematics and computer science, particularly in decision-making. This book explores the applications of advanced mathematical models and computational algorithms to AI-driven strategies and blockchain technologies.
It covers advanced linear algebra techniques, probability theory, optimization methods, game theory, cryptography, and statistical learning, providing deep mathematical insights into AI, blockchain, and data-driven decision-making. The book delves into matrix computations and eigenvalue problems relevant to deep learning, Bayesian inference for predictive modeling, and reinforcement learning for dynamic decision-making.
Additionally, optimization methods such as convex programming and Lagrangian multipliers enhance resource allocation, while cryptographic protocols ensure the security of blockchain systems. By integrating these mathematical frameworks, this book provides researchers, professionals, and students with practical tools for addressing complex business challenges ranging from fraud detection to automated contract execution.
Zielgruppe
Researchers, Professionals and Practitioners, Postgraduates




