Introduction To Linear Algebra 6th Edition Pdf Github


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Linear Algebra for Everyone


Linear Algebra for Everyone

Author: Gilbert Strang

language: en

Publisher: Wellesley-Cambridge Press

Release Date: 2020-11-26


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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.

Introduction to Applied Linear Algebra


Introduction to Applied Linear Algebra

Author: Stephen Boyd

language: en

Publisher: Cambridge University Press

Release Date: 2018-06-07


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A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

Mathematics for Machine Learning


Mathematics for Machine Learning

Author: Marc Peter Deisenroth

language: en

Publisher: Cambridge University Press

Release Date: 2020-04-23


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Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.