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＜電子ブック＞
Linear Algebra in Data Science / by Peter Zizler, Roberta La Haye
(Compact Textbooks in Mathematics. ISSN:2296455X)

版	1st ed. 2024.
出版者	(Cham : Springer International Publishing : Imprint: Birkhäuser)
出版年	2024
本文言語	英語
大きさ	VIII, 199 p. 23 illus., 9 illus. in color : online resource
著者標目	*Zizler, Peter author La Haye, Roberta author SpringerLink (Online service)
件　名	LCSH:Algebras, Linear LCSH:Artificial intelligence -- Data processing  全ての件名で検索 LCSH:Computer science -- Mathematics  全ての件名で検索 FREE:Linear Algebra FREE:Data Science FREE:Mathematical Applications in Computer Science
一般注記	This textbook explores applications of linear algebra in data science at an introductory level, showing readers how the two are deeply connected. The authors accomplish this by offering exercises that escalate in complexity, many of which incorporate MATLAB. Practice projects appear as well for students to better understand the real-world applications of the material covered in a standard linear algebra course. Some topics covered include singular value decomposition, convolution, frequency filtering, and neural networks. Linear Algebra in Data Science is suitable as a supplement to a standard linear algebra course HTTP:URL=https://doi.org/10.1007/978-3-031-54908-3

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