Applied mathematics with open-source software : operational research problems with Python and R / authored by Vincent Knight, Cardiff University, United Kingdom, Geraint Palmer, Cardiff University, United Kingdom.
Material type:
TextSeries: Chapman & Hall/CRC series in operations researchPublication details: Boca Raton, Chapman & Hall/CRC, c2022Edition: First editionDescription: 142 pages: illustrations (black and white); 27 cmISBN: 9780367339982 (paperback)Subject(s): Operations research -- Data processing | Mathematics -- Data processing | Python (Computer program language) | R (Computer program language)Additional physical formats: Online version:: Applied mathematics with open-source softwareDDC classification: 658.4/0340285 LOC classification: T57.5 | .K55 2022Summary: "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. 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"--
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
Staff Circulation
|
APU Library Open Shelf | Book | T57.5 .K55 2022 c.1 (Browse shelf (Opens below)) | 1 | Available | 00013022 | |
General Circulation
|
APU Library Open Shelf | Book | T57.5 .K55 2022 c.2 (Browse shelf (Opens below)) | 2 | Processing | 00013023 |
Includes bibliographical references and index.
"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. 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"--
There are no comments on this title.