Applied mathematics with open-source software : operational research problems with Python and R /

Applied Mathematics with Open-source Software: Operational Research Problems with Python and R is aimed at a broad segment of readers who wish to learn how to use open-source software to solve problems in applied mathematics. The book has an innovative structure with 4 sections of two chapters cover...

Full description

Bibliographic Details
Main Authors: Knight, Vincent (Vincent A.) (Author), Palmer, Geraint (Author)
Corporate Author: Taylor & Francis
Format: eBook
Language:English
Published: Boca Raton : CRC Press, 2022.
Edition:First edition.
Series:Chapman & Hall/CRC series in operations research
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:Applied Mathematics with Open-source Software: Operational Research Problems with Python and R is aimed at a broad segment of readers who wish to learn how to use open-source software to solve problems in applied mathematics. The book has an innovative structure with 4 sections of two chapters covering a large range of applied mathematical techniques: probabilistic modelling, dynamical systems, emergent behaviour and optimisation. The pairs of chapters in each section demonstrate different families of solution approaches. Each chapter starts with a problem, gives an overview of the relevant theory, shows a solution approach in R and in Python, and finally gives wider context by including a number of published references. This structure will allow for maximum accessibility, with minimal prerequisites in mathematics or programming as well as giving the right opportunities for a reader wanting to delve deeper into a particular topic. Features An excellent resource for scholars of applied mathematics and operational research, and indeed any academics who want to learn how to use open-source software. Offers more general and accessible treatment of the subject than other texts, both in terms of programming language but also in terms of the subjects considered. The R and Python sections purposefully mirror each other so that a reader can read only the section that interests them. An accompanying open-source repository with source files and further examples is posted online at https://bit.ly/3kpoKSd.
Physical Description:1 online resource (x, 142 pages).
Bibliography:Includes bibliographical references and index.
ISBN:9780429328534
0429328532
9781000582055
1000582051
9781000582109
1000582108