Computational Mathematics: An introduction to Numerical Analysis and Scientific Computing with Python

Computational Mathematics (Advances in Applied Mathematics)
Author: Dimitrios Mitsotakis (Author)
Edition 版本:‏ 1st
Publication Date 出版日期:‏ 2023-06-19
Language 语言: English
Print Length 页数: 528 pages
ISBN-10: 1032262397
ISBN-13: 9781032262390

Book Description

This textbook is a comprehensive introduction to computational mathematics and scientific computing suitable for undergraduate and postgraduate courses. It presents both practical and theoretical aspects of the subject, as well as advantages and pitfalls of classical numerical methods alongside with computer code and experiments in Python. Each chapter closes with modern applications in physics, engineering, and computer science.

Features:

  • No previous experience in Python is required.
  • Includes simplified computer code for fast-paced learning and transferable skills development.
  • Includes practical problems ideal for project assignments and distance learning.
  • Presents both intuitive and rigorous faces of modern scientific computing.
  • Provides an introduction to neural networks and machine learning.

From the Author

Computational mathematics is a branch of applied mathematics that focuses on solving mathematical problems using computers. It encompasses numerical modeling, the development and validation of numerical methods, and conducting numerical simulations. Given the ubiquitous presence of computers in modern science, a solid understanding of this subject is essential. If you are studying the theory and practice of scientific computations and numerical analysis, you will find the book “Computational Mathematics: An Introduction to Numerical Analysis and Scientific Computing with Python” to be highly beneficial. This book serves as an educational resource for students and researchers who are eager to swiftly and comprehensively learn one of the most powerful programming languages, as well as explore the fundamental tools and methods of computational mathematics. Within this book, you will encounter proofs and techniques that are not commonly found in traditional numerical analysis textbooks, accompanied by straightforward implementations in Python. It is suitable for students in natural sciences and engineering fields. Additionally, the book covers advanced topics, including an introduction to neural networks and eigenvalue problems, with practical applications to search engines.

About the Author

Dimitrios Mitsotakis received a PhD in Mathematics in 2007 from the University of Athens. His experience with high-performance computing started while at the Edinburgh Parallel Computing Center at the University of Edinburgh. Dimitrios worked at the University Paris-Sud as a Marie Curie fellow, at the University of Minnesota as an associate postdoc and at the University of California, Merced as a Visiting Assistant Professor. Dimitrios is currently an associate professor/reader at the School of Mathematics and Statistics of Victoria University of Wellington. He has published his work in journals of numerical analysis and in more general audience journals in physics, coastal engineering, waves sciences, and in scientific computing. He develops numerical methods for the solution of equations for water waves, and he studies real-world applications such as the generation of tsunamis. Some of his main contributions are in the theory and numerical analysis of Boussinesq systems for nonlinear and dispersive water waves.

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