Titlebook: Numerical Python; Scientific Computing Robert Johansson Book 2024Latest edition Robert Johansson 2024 Python.numerical.NumPy.SciPy.computat

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Interpolation,approximate complicated functions, which, for example, could be computationally demanding to evaluate. In that case, evaluating the original function only at a limited number of points and using interpolation to approximate the function when evaluating it for intermediary points can be beneficial.

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Bayesian Statistics,it is generally true that statistical problems can, in principle, be solved using either frequentist or Bayesian statistics, practical differences make these two approaches to statistics suitable for different types of problems.

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979-8-8688-0412-0Robert Johansson 2024

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Robert JohanssonRevised and updated with examples using the numerical and mathematical modules in Python and its standard library.Understand open-source numerical Python packages like NumPy, SciPy, SymPy, matplotlib

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Equation Solving,The previous chapters discussed general methodologies and techniques, namely, array-based numerical computing, symbolic computing, and visualization. These methods are the cornerstones of scientific computing that make up a fundamental toolset we have at our disposal when attacking computational problems.

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https://doi.org/10.1007/979-8-8688-0413-7Python; numerical; NumPy; SciPy; computation; algorithms; FEniCS; TensorFlow; Signal Processing; Image Proces

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