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"Approximation and interpolation" is a technical book category focused on the theory, methods, and applications for representing, estimating, and reconstructing functions and data when exact forms are unavailable or impractical. Works in this category cover classical and modern topics such as polynomial and spline interpolation, least-squares and Chebyshev approximation, constructive and functional approximation theory, wavelets and basis expansions, radial basis functions and meshless methods, and numerical techniques used in signal processing, scientific computing, and data fitting. Emphasis is placed on error analysis, stability, convergence rates, and algorithmic implementation, often bridging rigorous mathematics with practical computational tools and software. Books range from introductory textbooks for students through advanced monographs for researchers and practitioners in applied mathematics, engineering, computer graphics, statistics, and machine learning.

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