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Introduction to Applied Linear Algebra
This book is meant to provide an introduction to vectors, matrices, and least squares methods, basic topics in applied linear algebra. Our goal is to give the beginning student, with little or no prior exposure to linear algebra, a good grounding in the basic ideas, as well as an appreciation for how they are used in many applications, including data fitting, machine learning and artificial intelligence, tomography, image processing, finance, and automatic control systems. Topics covered includes, Vectors, Norm and distance, Clustering, Matrices, Linear equations, Matrix multiplication, Linear dynamical systems, Least squares, Multiobjective least squares, Constrained least squares.
Author(s): Stephen Boyd and Lieven Vandenberghe
473 Pages
This book contains below topics, Vector Spaces, Finite Dimensional Vector Spaces, Linear Maps, Polynomials, Eigenvalues and Eigenvectors, Inner Product Spaces, Operators on Inner Product Spaces, Operators on Complex Vector Spaces, Operators on Real Vector Spaces, Trace and Determinant.
Author(s): Sheldon Axler
404 Pages
This book contains below topics, Systems of Linear Equations, Vectors, Matrices, Linear Transformations, Vector Spaces, Determinants, Eigenvalues and Eigenvectors, Orthogonality.
Author(s): David Cherney, Tom Denton, Rohit Thomas, Andrew Waldron
395 Pages
This book contains below topics, Systems of Linear Equations, Row Reduction, Vector Geometry, Linear Transformations, Eigenvalues, Orthogonality, Determinants.
Author(s): Dan Margalit and Joseph Rabinoff
455 Pages
A First Course in Linear Algebra Study Guide for the Undergraduate Linear Algebra Course
This book contains below topics, Systems of Linear Equations, Vector Spaces, Homogeneous Systems, Characteristic Equation of Matrix, Matrix Dot Product.
Author(s): Mohammed K A Kaabar
132 Pages
Lecture Notes on Randomized Linear Algebra
This note contains below topics, Approximating Matrix Multiplication, Scalar and Matrix Concentration, Concentration and Matrix Multiplication, Matrix Multiplication and Random Projections, Sampling and Projections for Least squares Approximation, Fast Random Projections and FJLT, Randomized Least squares Approximation in Practice, Additive error Low rank Matrix Approximation, Relative error Low rank Matrix Approximation, Randomized Low rank Approximation in Practice, Low rank Matrix Approximation with Element wise Sampling, Element wise Sampling and Matrix Completion, Element wise Sampling of Graphs and Linear Equation Solving.
Author(s): Michael W. Mahoney
188 Pages
Advanced Linear Algebra by David Surowski
This note explains the following topics, Eigenvalues and Eigenvectors, The spectral theorem, Tensor Products, Fourier Analysis and Quadrtic Reciprocity.
Author(s): David Surowski
157 Pages
Exercises and Problems in Linear Algebra
This collection of exercises is designed to provide a framework for discussion in a junior level linear algebra class conducted fairly regularly at Portland State University. Topics covered includes, Matrices And Linear Equations, Vector Spaces, Linear Maps Between Vector Spaces, Spectral Theory Of Vector Spaces, The Geometry Of Inner Product Spaces, Adjoint Operators, Spectral Theory Of Inner Product Spaces.
Author(s): John M. Erdman
196 Pages
