國立高雄大學圖資館 |

Language: English

Back

Linear algebra with python :modern computational approaches /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Linear algebra with python :G. R. Liu.
Reminder of title:	modern computational approaches /
Author:	Liu, Gui-Rong,
Published:	Mason, USA :ScienTech Publisher,c2026.
Description:	xii, 459 p. :ill. (some col.) ;27 cm.
Subject:	Algebras, Linear.
ISBN:	9781946018076 :

Linear algebra with python :modern computational approaches /
Liu, Gui-Rong,1958-

Linear algebra with python :modern computational approaches /G. R. Liu. - 1st ed. - Mason, USA :ScienTech Publisher,c2026. - xii, 459 p. :ill. (some col.) ;27 cm.

Includes bibliographical references and index.

"This book provides a comprehensive exploration of the fundamental principles of linear algebra, with a particular focus on different types of systems and matrices, including: Indeterminate systems; Determined systems; Overdetermined systems; Underdetermined systems; Eigenvalue Decomposition (EVD); Singular Value Decomposition (SVD); and Moore-Penrose pseudo-inverse. Each topic is explained in depth, enriched by the author's extensive experience in research and teaching. Beyond classical methods, the book introduces innovative concepts, such as the Inverse Relationship Theorem and the alpha-method for tackling indeterminate systems, providing readers with powerful new tools for problem-solving. Designed for diverse learning environments, such as classroom instruction, online courses, or self-study, the book combines rigorous theory with practical applications. Python code examples are integrated throughout, allowing readers to see how mathematical concepts translate directly into formulas, numericl results, and visualizations. Readers are encouraged to experiment with the code to deepen understanding and develop their own solutions for related problems. Presented in Jupyter Notebook format, this book seamlessly unites theoretical explanations, mathematical formulations, and executable code in a single interactive document. This creates an engaging environment for learning, practicing, and exploring concepts in real time. Heavy lifting in formula derivation and number crunching is handled by the computer, allowing readers to focus more on understanding the concepts"--

ISBN: 9781946018076 :NT$9459

LCCN: 2026938251Subjects--Topical Terms:

183087
Algebras, Linear.

LC Class. No.: QA184.2 / L783 2026

Linear algebra with python :modern computational approaches /
LDR:02179cam a2200181 a 4500 001 694747
005 20260611210302.6
008 261007s2026 ohua b 001 0 eng
010 $a 2026938251
020 $a 9781946018076 : $c NT$9459
035 $a in00024517247
040 $a DLC $b eng $c DLC
050 4 $a QA184.2 $b L783 2026
100 1 $a Liu, Gui-Rong, $d 1958- $e author. $3 1011779
245 1 0 $a Linear algebra with python : $b modern computational approaches / $c G. R. Liu.
250 $a 1st ed.
260 $a Mason, USA : $b ScienTech Publisher, $c c2026.
300 $a xii, 459 p. : $b ill. (some col.) ; $c 27 cm.
504 $a Includes bibliographical references and index.
520 $a "This book provides a comprehensive exploration of the fundamental principles of linear algebra, with a particular focus on different types of systems and matrices, including: Indeterminate systems; Determined systems; Overdetermined systems; Underdetermined systems; Eigenvalue Decomposition (EVD); Singular Value Decomposition (SVD); and Moore-Penrose pseudo-inverse. Each topic is explained in depth, enriched by the author's extensive experience in research and teaching. Beyond classical methods, the book introduces innovative concepts, such as the Inverse Relationship Theorem and the alpha-method for tackling indeterminate systems, providing readers with powerful new tools for problem-solving. Designed for diverse learning environments, such as classroom instruction, online courses, or self-study, the book combines rigorous theory with practical applications. Python code examples are integrated throughout, allowing readers to see how mathematical concepts translate directly into formulas, numericl results, and visualizations. Readers are encouraged to experiment with the code to deepen understanding and develop their own solutions for related problems. Presented in Jupyter Notebook format, this book seamlessly unites theoretical explanations, mathematical formulations, and executable code in a single interactive document. This creates an engaging environment for learning, practicing, and exploring concepts in real time. Heavy lifting in formula derivation and number crunching is handled by the computer, allowing readers to focus more on understanding the concepts"-- $c Provided by publisher.
650 0 $a Algebras, Linear. $3 183087
650 0 $a Python (Computer program language) $3 215247