An Introduction to Scientific Computing with MATLAB® and Python Tutorials
eBook - ePub

An Introduction to Scientific Computing with MATLAB® and Python Tutorials

  1. 384 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

An Introduction to Scientific Computing with MATLAB® and Python Tutorials

About this book

This textbook is written for the first introductory course on scientific computing. It covers elementary numerical methods for linear systems, root finding, interpolation, numerical integration, numerical differentiation, least squares problems, initial value problems and boundary value problems. It includes short Matlab and Python tutorials to quickly get students started on programming. It makes the connection between elementary numerical methods with advanced topics such as machine learning and parallel computing.

This textbook gives a comprehensive and in-depth treatment of elementary numerical methods. It balances the development, implementation, analysis and application of a fundamental numerical method by addressing the following questions.

•Where is the method applied?
•How is the method developed?
•How is the method implemented?
•How well does the method work?

The material in the textbook is made as self-contained and easy-to-follow as possible with reviews and remarks. The writing is kept concise and precise. Examples, figures, paper-and-pen exercises and programming problems are deigned to reinforce understanding of numerical methods and problem-solving skills.

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Yes, you can access An Introduction to Scientific Computing with MATLAB® and Python Tutorials by Sheng Xu in PDF and/or ePUB format, as well as other popular books in Mathematics & Mathematics General. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover Page
  2. Half-Title Page
  3. Title Page
  4. Copyright Page
  5. Dedication Page
  6. Contents
  7. Preface
  8. Author
  9. 1 An Overview of Scientific Computing
  10. 2 Taylor's Theorem
  11. 3 Roundoff Errors and Error Propagation
  12. 4 Direct Methods for Linear Systems
  13. 5 Root Finding for Nonlinear Equations
  14. 6 Interpolation
  15. 7 Numerical Integration
  16. 8 Numerical Differentiation
  17. 9 Initial Value Problems and Boundary Value Problems
  18. 10 Basic Iterative Methods for Linear Systems
  19. 11 Discrete Least Squares Problems
  20. 12 Monte Carlo Methods and Parallel Computing
  21. Appendices
  22. Index