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.
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