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Introduction to Applied Linear Algebra. Vectors, Matrices, and Least Squares by Stephen Boyd, Lieven Vandenberghe is a mathematics available to read on EtoBox.

What is Introduction to Applied Linear Algebra. Vectors, Matrices, and Least Squares about?

Cover Contents Preface I Vectors Vectors Vectors Vector addition Scalar-vector multiplication Inner product Complexity of vector computations Exercises Linear functions Linear functions Taylor approximation Regression model Exercises Norm and distance Norm Distance Standard deviation Angle Complexity Exercises Clustering Clustering A clustering objective The k-means algorithm Examples Applications Exercises Linear independence Linear dependence Basis Orthonormal vectors Gram–Schmidt algorithm Exercises II Matrices Matrices Matrices Zero and identity matrices Transpose, addition, and norm Matrix-vector multiplication Complexity Exercises Matrix examples Geometric transformations Selectors Incidence matrix Convolution Exercises Linear equations Linear and affine functions Linear function models Systems of linear equations Exercises Linear dynamical systems Linear dynamical systems Population dynamics Epidemic dynamics Motion of a mass Supply chain dynamics Exercises Matrix multiplication Matrix-matrix multiplication Composition of linear functions Matrix power QR factorization Exercises Matrix inverses Left and right inverses Inverse Solving linear equations Examples Pseudo-inverse E

Who reads Introduction to Applied Linear Algebra. Vectors, Matrices, and Least Squares?

Author

Stephen Boyd, Lieven Vandenberghe

Publisher

Cambridge University Press

Published

2018

Language

EN

Category

mathematics

Subjects

Mathematics, Algebra, Stem

Rating

4.4 / 5 (90 ratings)

Updated

2026-03-14