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Applied Mathematics with Open-Source Software

Operational Research Problems with Python and R

Jezik AngleščinaAngleščina
E-knjiga Adobe ePub DRM
E-knjiga Applied Mathematics with Open-Source Software Vincent Knight
Koda Libristo: 39871511
Založba Chapman and Hall/CRC, maj 2022
Applied Mathematics with Open-source Software: Operational Research Problems with Python and R is ai... Celoten opis
? points 160 b
66.22
Na zalogi Prenesi zdaj

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.FeaturesAn 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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Polni naslov Applied Mathematics with Open-Source Software
Jezik Angleščina
Vezava E-knjiga - Adobe ePub DRM
Datum izida 2022
Število strani 142
EAN 9781000582109
Koda Libristo 39871511
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