Applied Numerical Methods with Python for Engineers and Scientists 1st Edition (ISE) By Steven C. Chapra, David Clough
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Applied Numerical Methods with Python for Engineers and Scientists 1st Edition (ISE) By Steven C. Chapra, David Clough

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About this ebook
The Applied Numerical Methods with Python for Engineers and Scientists (1st Edition, International Student Edition/ISE) by Steven C. Chapra and David E. Clough is structured into six core parts that transition engineering problem-solving principles into the Python programming language. [1, 2, 3]
The complete breakdown of the chapters and topics covered in the textbook includes: [1]
  • Part One: Modeling, Computers, and Error Analysis (Chapters 1–4): Covers mathematical modeling, Python fundamentals and programming (Spyder/IPython, syntax, functions, and control flow), alongside roundoff and truncation errors and Taylor series. [1, 2]
  • Part Two: Roots and Optimization (Chapters 5–7): Focuses on bracketing methods (bisection, false-position), open methods (Newton-Raphson, secant), and optimization techniques. [1]
  • Part Three: Linear Systems (Chapters 8–13): Explores linear algebraic equations, Gauss elimination, LU factorization, matrix inversion and condition numbers, iterative methods (Gauss-Seidel, Jacobi), and eigenvalues. [1]
  • Part Four: Curve Fitting (Chapters 14–18): Details linear and nonlinear regression, Fourier analysis, polynomial interpolation (Newton and Lagrange), and splines/piecewise interpolation. [1, 2]
  • Part Five: Integration and Differentiation (Chapters 19–21): Reviews Newton-Cotes integration formulas (Trapezoidal, Simpson's rules), function integration via Gauss quadrature and adaptive methods, and numerical differentiation. [1]
  • Part Six: Ordinary Differential Equations (Chapters 22–24): Addresses initial-value problems (Euler, Runge-Kutta), adaptive and stiff systems, and boundary-value problems. [1]

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9781265017965 adaptive and stiff systems Curve Fitting Details linear and nonlinear regression Integration and Differentiation Reviews Newton-Cotes integration formulas Ordinary Differential Equations Addresses initial-value problems Linear Systems Explores linear algebraic equations Modeling Computers and Error Analysis mathematical modeling Python fundamentals and programming Roots and Optimization bracketing methods
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