Abstract
This article investigates the theoretical and practical aspects of constructing the Newton interpolation polynomial, a key method for function approximation. Furthermore, it demonstrates the steps for determining coefficients by constructing a system of linear equations based on given datasets. In the practical section, Python programming code and algorithms for calculating the Newton polynomial using the Gauss elimination method are provided
References
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