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Numerical computing is a practical, interdisciplinary book category focused on algorithms and methods for solving mathematical problems approximately on computers, emphasizing accuracy, stability, efficiency, and error analysis. Titles in this area cover core topics such as numerical linear algebra, root-finding, numerical integration and differentiation, ordinary and partial differential equations, optimization, eigenvalue problems, interpolation and approximation, and the effects of finite-precision (floating-point) arithmetic. Books range from rigorous numerical analysis texts and algorithmic references to hands-on implementation guides and software manuals (e.g., LAPACK, BLAS, NumPy), and include applied case studies in engineering, physics, data science, and finance. Intended readers include advanced undergraduates, graduate students, researchers, and practitioners who have a grounding in calculus and linear algebra and want to understand both the mathematical foundations and practical coding considerations for reliable computational solutions.

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