[center]Linear Algebra with Python | 315 | Makoto Tsukada, Yuji Kobayashi, Hiroshi Kaneko, Sin-Ei Takahasi, Kiyoshi Shirayanagi, Masato Noguchi | 2023 | Springer Nature Singapore | [/align]
This textbook is for those who want to learn linear algebra from the basics. After a brief mathematical introduction, it provides the standard curriculum of linear algebra based on an abstract linear space. It covers, among other aspects: linear mappings and their matrix representations, basis, and dimension; matrix invariants, inner products, and norms; eigenvalues and eigenvectors; and Jordan normal forms. Detailed and self-contained proofs as well as descriptions are given for all theorems, formulas, and algorithms.
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⭐️ 978-981-99-2951-1.epub (68.62 MB)
⭐️ 978-981-99-2951-1.pdf (8.26 MB)
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✅ Linear Algebra with Python Theory and Applications (76.88 MB)
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