Computational discovery on Jupyter

By:

Calkin, Neil J

Contributor(s):

Publication details: Philadelphia: Society for Industrial and Applied Mathematics (SIAM), 2024.Description: xviii, 397p.: col. ill.; pbk.: 28 cmISBN:

9781611977493

Subject(s):

DDC classification:

510.28553 CAL

Summary: This book uses Python to teach mathematics not found in the standard curriculum, so students learn a popular programming language as well as some interesting mathematics. Videos, images, programs, programming activities, pencil-and-paper activities, and associated Jupyter Notebooks accompany the text, and readers are encouraged to interact with and extend the material as well as contribute their own notebooks. Indeed, some of the material was created/discovered/invented/published first by the authors’ students. Useful pedagogical features include: using an active learning approach with topics not typically found in a standard math curriculum introducing concepts using programming, not proof, with the goal of preparing readers for the need for proof accompanying all activities with a full discussion Audience Computational Discovery on Jupyter is for upper-level high school and lower-level college students. Graduate students in mathematics will also find it of interest. https://epubs.siam.org/doi/book/10.1137/1.9781611977509

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Barcode
Books	IIT Gandhinagar	General	510.28553 CAL (Browse shelf(Opens below))	1	Available	036319

Includes Bibliography, Acknowledgements and Index.

This book uses Python to teach mathematics not found in the standard curriculum, so students learn a popular programming language as well as some interesting mathematics. Videos, images, programs, programming activities, pencil-and-paper activities, and associated Jupyter Notebooks accompany the text, and readers are encouraged to interact with and extend the material as well as contribute their own notebooks. Indeed, some of the material was created/discovered/invented/published first by the authors’ students.

Useful pedagogical features include:

using an active learning approach with topics not typically found in a standard math curriculum

introducing concepts using programming, not proof, with the goal of preparing readers for the need for proof

accompanying all activities with a full discussion

Audience

Computational Discovery on Jupyter is for upper-level high school and lower-level college students. Graduate students in mathematics will also find it of interest.

https://epubs.siam.org/doi/book/10.1137/1.9781611977509

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