Inhaltsangabe
From Gilbert Strang, a new approach to linear algebra that is suitable for everyone, going from basics to the singular value decomposition.
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Über die Autorin bzw. den Autor
Gilbert Strang has been teaching Linear Algebra at Massachusetts Institute of Technology (MIT) for over fifty years. His online lectures for MIT's OpenCourseWare have been viewed over ten million times. He is a former President of the Society for Industrial and Applied Mathematics and Chair of the Joint Policy Board for Mathematics. Professor Strang is the author of twelve books, including the bestselling classic Introduction to Linear Algebra (2016), now in its fifth edition.
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Linear Algebra for Everyone
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ISBN 13: 9781733146630
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Linear Algebra for Everyone
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Gebunden. Zustand: New. From Gilbert Strang, a new approach to linear algebra that is suitable for everyone, going from basics to the singular value decomposition.Linear algebra has become the subject to know for people in quantitative disciplines of all kinds. No longer the e. Artikel-Nr. 406732087
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Linear Algebra for Everyone
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Cambridge University Pr. Nov 2020, 2020
ISBN 10: 1733146636
ISBN 13: 9781733146630
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Buch. Zustand: Neu. Neuware -Linear algebra has become the subject to know for people in quantitative disciplines of all kinds. No longer the exclusive domain of mathematicians and engineers, it is now used everywhere there is data and everybody who works with data needs to know more. This new book from Professor Gilbert Strang, author of the acclaimed Introduction to Linear Algebra, now in its fifth edition, makes linear algebra accessible to everybody, not just those with a strong background in mathematics. It takes a more active start, beginning by finding independent columns of small matrices, leading to the key concepts of linear combinations and rank and column space. From there it passes on to the classical topics of solving linear equations, orthogonality, linear transformations and subspaces, all clearly explained with many examples and exercises. The last major topics are eigenvalues and the important singular value decomposition, illustrated with applications to differential equations and image compression. A final optional chapter explores the ideas behind deep learning.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 368 pp. Englisch. Artikel-Nr. 9781733146630
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Buch. Zustand: Neu. Linear Algebra for Everyone | Gilbert Strang | Buch | Gebunden | Englisch | 2021 | Cambridge University Pr. | EAN 9781733146630 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. Artikel-Nr. 119060759
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Buch. Zustand: Neu. Neuware - Linear algebra has become the subject to know for people in quantitative disciplines of all kinds. No longer the exclusive domain of mathematicians and engineers, it is now used everywhere there is data and everybody who works with data needs to know more. This new book from Professor Gilbert Strang, author of the acclaimed Introduction to Linear Algebra, now in its fifth edition, makes linear algebra accessible to everybody, not just those with a strong background in mathematics. It takes a more active start, beginning by finding independent columns of small matrices, leading to the key concepts of linear combinations and rank and column space. From there it passes on to the classical topics of solving linear equations, orthogonality, linear transformations and subspaces, all clearly explained with many examples and exercises. The last major topics are eigenvalues and the important singular value decomposition, illustrated with applications to differential equations and image compression. A final optional chapter explores the ideas behind deep learning. Artikel-Nr. 9781733146630
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 368 | Sprache: Englisch | Produktart: Bücher | Linear algebra has become the subject to know for people in quantitative disciplines of all kinds. No longer the exclusive domain of mathematicians and engineers, it is now used everywhere there is data and everybody who works with data needs to know more. This new book from Professor Gilbert Strang, author of the acclaimed Introduction to Linear Algebra, now in its fifth edition, makes linear algebra accessible to everybody, not just those with a strong background in mathematics. It takes a more active start, beginning by finding independent columns of small matrices, leading to the key concepts of linear combinations and rank and column space. From there it passes on to the classical topics of solving linear equations, orthogonality, linear transformations and subspaces, all clearly explained with many examples and exercises. The last major topics are eigenvalues and the important singular value decomposition, illustrated with applications to differential equations and image compression. A final optional chapter explores the ideas behind deep learning. Artikel-Nr. 36887190/2
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Linear Algebra for Everyone
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Cambridge University Pr. Nov 2020, 2020
ISBN 10: 1733146636
ISBN 13: 9781733146630
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Buch. Zustand: Neu. Neuware -Linear algebra has become the subject to know for people in quantitative disciplines of all kinds. No longer the exclusive domain of mathematicians and engineers, it is now used everywhere there is data and everybody who works with data needs to know more. This new book from Professor Gilbert Strang, author of the acclaimed Introduction to Linear Algebra, now in its fifth edition, makes linear algebra accessible to everybody, not just those with a strong background in mathematics. It takes a more active start, beginning by finding independent columns of small matrices, leading to the key concepts of linear combinations and rank and column space. From there it passes on to the classical topics of solving linear equations, orthogonality, linear transformations and subspaces, all clearly explained with many examples and exercises. The last major topics are eigenvalues and the important singular value decomposition, illustrated with applications to differential equations and image compression. A final optional chapter explores the ideas behind deep learning. 368 pp. Englisch. Artikel-Nr. 9781733146630
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