Intuitively Understand the Basics of Linear Algebra with Abundant Diagrams! Publication of 'Illustrated Linear Algebra: The Strang Method for Intuitive Understanding'

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On April 22, 2026, Kindai Kagaku Sha published 'Illustrated Linear Algebra' by Kenji Hiranabe. Inspired by MIT's Professor Gilbert Strang, this introductory book visually elucidates essential matrix decompositions for machine learning.

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On April 22, 2026, Kindai Kagaku Sha published 'Illustrated Linear Algebra' by Kenji Hiranabe. Inspired by MIT's Professor Gilbert Strang, this introductory book visually elucidates essential matrix decompositions for machine learning.

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Source: https://prtimes.jp/main/html/rd/p/000007345.000005875.html | Date: Date unavailable

Kindai Kagaku Sha Co., Ltd., which operates a specialized book publishing business in the science and engineering fields under the Impress Group, announced the release of the book "Illustrated Linear Algebra" (Author: Kenji Hiranabe) from its Kindai Kagaku Sha Digital label (*) on April 22, 2026. *What is Kindai Kagaku Sha Digital: It is an on-demand publishing label utilizing digital technology, where Kindai Kagaku Sha collaborates with authors in a project-based style. Please also see here for details. https://www.kindaikagaku.co.jp/kdd/scheme/ ● Bibliographic Information [Title] Illustrated Linear Algebra [Author] Kenji Hiranabe [Specifications] A5 size, regular binding, partially color in print / partially color in digital, 274 main pages [Standard Price (Print)] 3,300 yen (excluding tax) [Standard Price (Digital)] 3,300 yen (excluding tax) [ISBN] (Book with cover) 978-4-7649-0785-0 C3041 [ISBN] (POD) 978-4-7649-6140-1 C3041 [Product URL] https://www.kindaikagaku.co.jp/book_list/detail/9784764961401/ ● Content Introduction This book is an introductory text that aims for readers to intuitively master the essence of linear algebra, centering on the three elements of head (theory), hands (calculation), and eyes (illustration). The core of this book consists of the "4 subspaces" serving as a map overlooking the world of linear algebra, and the "5 matrix decompositions (LU, CR, QR, Eigenvalue, and Singular Value Decomposition)" which are extremely important in practice. In each chapter, the book starts with concrete example problems, interweaving detailed explanations of theorems with intuitive visual commentaries, structured so readers can steadily step up. In particular, the CR decomposition that vividly unravels the properties of a matrix's rank, and the Singular Value Decomposition (SVD) that serves as the foundation of modern machine learning and data science, are positioned as the highlights of the book, offering an "Aha! experience" where the knowledge learned

Intuitively Understand the Basics of Linear Algebra with Abundant Diagrams! Publication of 'Illustrated Linear Algebra: The Strang Method for Intuitive Understanding'

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