Description

Book Synopsis
Applied Numerical Methods with Python, 1st Edition is written for students who want to learn and apply numerical methods in order to solve problems in engineering and science. As such, the methods are motivated by problems rather than by mathematics. Sufficient theory is provided so students come away with insight into the techniques and their shortcomings. If you have ever used Applied Numerical Methods for MATLAB, you'll find transitioning to this Python program seamless!

Table of Contents
1 Mathematical Modeling, Numerical Methods, and Problem Solving
2 Python Fundamentals
3 Programming in Python
4 Roundoff and Truncation Errors
5 Roots: Bracketing Methods
6 Roots: Open Methods
7 Optimization
8 Linear Algebraic Equations and Matrices
9 Gauss Elimination
10 LU Factorization
11 Matrix Inverse and Condition
12 Iterative Methods
13 Eigenvalues
14 Straight-Line Linear Regression
15 General Linear and Nonlinear Regression
16 Fourier Analysis
17 Polynomial Interpolation
18 Splines and Piecewise Interpolation
19 Numerical Integration Formulas
20 Numerical Integration of Functions
21 Numerical Differentiation
22 Initial-Value Problems
23 Adaptive Methods and Stiff Systems
24 Boundary-Value Problems

Applied Numerical Methods with Python for

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    A Paperback / softback by Steven Chapra, David Clough

    £56.04

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      Book details

      Publisher McGraw-Hill Education
      Published 29 December 2021
      ISBN-13 9781265017965
      978-1265017965
      ISBN-10 1265017964
      Also in:
      Technology, Engineering & Agriculture Civil engineering, surveying and building

      Description

      Book Synopsis
      Applied Numerical Methods with Python, 1st Edition is written for students who want to learn and apply numerical methods in order to solve problems in engineering and science. As such, the methods are motivated by problems rather than by mathematics. Sufficient theory is provided so students come away with insight into the techniques and their shortcomings. If you have ever used Applied Numerical Methods for MATLAB, you'll find transitioning to this Python program seamless!

      Table of Contents
      1 Mathematical Modeling, Numerical Methods, and Problem Solving
      2 Python Fundamentals
      3 Programming in Python
      4 Roundoff and Truncation Errors
      5 Roots: Bracketing Methods
      6 Roots: Open Methods
      7 Optimization
      8 Linear Algebraic Equations and Matrices
      9 Gauss Elimination
      10 LU Factorization
      11 Matrix Inverse and Condition
      12 Iterative Methods
      13 Eigenvalues
      14 Straight-Line Linear Regression
      15 General Linear and Nonlinear Regression
      16 Fourier Analysis
      17 Polynomial Interpolation
      18 Splines and Piecewise Interpolation
      19 Numerical Integration Formulas
      20 Numerical Integration of Functions
      21 Numerical Differentiation
      22 Initial-Value Problems
      23 Adaptive Methods and Stiff Systems
      24 Boundary-Value Problems

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