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Introduction to Applied Linear Algebra

Introduction to Applied Linear Algebra 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, Multi-objective least squares, Constrained least squares.

Author(s): 473 Pages Similar Books

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, Multi-objective least squares, Constrained least squares. 473 Pages

Linear Algebra Notes by David A. Santos

The purpose with these notes is to introduce students to the concept of proof in linear algebra in a gentle manner. Topics covered includes: Matrices and Matrix Operations, Linear Equations, Vector Spaces, Linear Transformations, Determinants, Eigenvalues and Eigenvectors, Linear Algebra and Geometry. 270 Pages

Linear Algebra II Lecture Notes (PDF 61P)

This book explains the following topics related to Linear Algebra: Vectors, Linear Equations, Matrix Algebra, Determinants, Eigenvalues and Eigenvectors, Linear Transformations, Dimension, Similarity and Diagonalizability, Complex Numbers, Projection Theorem, Gram-Schmidt Orthonormalization, QR Factorization, Least Squares Approximation, Orthogonal (Unitary) Diagonalizability, Systems of Differential Equations, Quadratic Forms, Vector Spaces and the Pseudoinverse. 61 Pages

Linear Algebra in Twenty Five Lectures (PDF 395P)

This note emphasize the concepts of vector spaces and linear transformations as mathematical structures that can be used to model the world around us. Topics covered includes: Gaussian Elimination, Elementary Row Operations, Vector Spaces, Linear Transformations, Matrices, Elementary Matrices and Determinants, Eigenvalues and Eigenvectors, Diagonalization, Kernel, Range, Nullity, Rank, Gram-Schmidt and Orthogonal Complements. 395 Pages

A Course In Algebraic Number Theory

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College Algebra 356 Pages

Course of Linear Algebra and Multidimensional Geometry

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This article reviews the basics of linear algebra and provides the reader with the foundation required for understanding most chemometrics literature. 27 Pages

A Course in Universal Algebra

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A Geometric Review of Linear Algebra

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Linear Algebra Hefferon J (Mirror)

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Elements of Abstract and Linear Algebra

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Algebra

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PROBLEMS IN ALGEBRAIC COMBINATORICS

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Basic Linear Algebra (PDF 73p)

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