Introduction to scientific computing and data analysis:
This textbook provides an introduction to numerical computing and its applications in science and engineering. The topics covered include those usually found in an introductory course, as well as those that arise in data analysis. This includes optimization and regression-based methods using a singu...
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cham, Switzerland
Springer
[2023]
|
| Edition: | Second edition |
| Series: | Texts in computational science and engineering
Volume 13 |
| Subjects: | |
| Summary: | This textbook provides an introduction to numerical computing and its applications in science and engineering. The topics covered include those usually found in an introductory course, as well as those that arise in data analysis. This includes optimization and regression-based methods using a singular value decomposition. The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used. The codes used for most of the computational examples in the text are available on GitHub. This new edition includes material necessary for an upper division course in computational linear algebra |
| Item Description: | Preface.- Preface to Second Edition.- Introduction to Scientific Computing.- Solving a Nonlinear Equation.- Matrix Equations.- Eigenvalue Problems.- Interpolation.- Numerical Integration.- Initial Value Problems.- Optimization: Regression.- Optimization: Descent Methods.- Data Analysis.- Taylor's Theorem.- Vector and Matrix Summary.- Answers.- References.- Index |
| Physical Description: | xvi, 554 Seiten Illustrationen, Diagramme 1120 grams |
| ISBN: | 9783031224294 |
Staff View
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| id | DE-604.BV049100360 |
| illustrated | Illustrated |
| index_date | 2024-07-03T22:32:28Z |
| indexdate | 2024-07-10T09:55:20Z |
| institution | BVB |
| isbn | 9783031224294 |
| language | English |
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| oclc_num | 1401184987 |
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| owner_facet | DE-29T |
| physical | xvi, 554 Seiten Illustrationen, Diagramme 1120 grams |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | Springer |
| record_format | marc |
| series | Texts in computational science and engineering |
| series2 | Texts in computational science and engineering |
| spelling | Holmes, Mark H. Verfasser (DE-588)1107050499 aut Introduction to scientific computing and data analysis Mark H. Holmes Second edition Cham, Switzerland Springer [2023] xvi, 554 Seiten Illustrationen, Diagramme 1120 grams txt rdacontent n rdamedia nc rdacarrier Texts in computational science and engineering Volume 13 Preface.- Preface to Second Edition.- Introduction to Scientific Computing.- Solving a Nonlinear Equation.- Matrix Equations.- Eigenvalue Problems.- Interpolation.- Numerical Integration.- Initial Value Problems.- Optimization: Regression.- Optimization: Descent Methods.- Data Analysis.- Taylor's Theorem.- Vector and Matrix Summary.- Answers.- References.- Index This textbook provides an introduction to numerical computing and its applications in science and engineering. The topics covered include those usually found in an introductory course, as well as those that arise in data analysis. This includes optimization and regression-based methods using a singular value decomposition. The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used. The codes used for most of the computational examples in the text are available on GitHub. This new edition includes material necessary for an upper division course in computational linear algebra bicssc bisacsh Mathematical optimization Mathematical analysis Mathematics—Data processing Hardcover, Softcover / Informatik, EDV/Allgemeines, Lexika Erscheint auch als Online-Ausgabe 978-3-031-22430-0 Vorangegangen ist 978-3-319-30254-6 Texts in computational science and engineering Volume 13 (DE-604)BV016971315 13 |
| spellingShingle | Holmes, Mark H. Introduction to scientific computing and data analysis Texts in computational science and engineering bicssc bisacsh Mathematical optimization Mathematical analysis Mathematics—Data processing |
| title | Introduction to scientific computing and data analysis |
| title_auth | Introduction to scientific computing and data analysis |
| title_exact_search | Introduction to scientific computing and data analysis |
| title_exact_search_txtP | Introduction to scientific computing and data analysis |
| title_full | Introduction to scientific computing and data analysis Mark H. Holmes |
| title_fullStr | Introduction to scientific computing and data analysis Mark H. Holmes |
| title_full_unstemmed | Introduction to scientific computing and data analysis Mark H. Holmes |
| title_short | Introduction to scientific computing and data analysis |
| title_sort | introduction to scientific computing and data analysis |
| topic | bicssc bisacsh Mathematical optimization Mathematical analysis Mathematics—Data processing |
| topic_facet | bicssc bisacsh Mathematical optimization Mathematical analysis Mathematics—Data processing |
| volume_link | (DE-604)BV016971315 |
| work_keys_str_mv | AT holmesmarkh introductiontoscientificcomputinganddataanalysis |