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Linear Algebra

1977-06-01 Mathematics
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Release : 1977-06-01
Genre : Mathematics
Kind : eBook
Book Rating : 187/5 ( reviews)

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Book Synopsis Linear Algebra by : Georgi? Evgen?evich Shilov

Download or read book Linear Algebra written by Georgi? Evgen?evich Shilov. This book was released on 1977-06-01. Available in PDF, EPUB and Kindle. Book excerpt: Covers determinants, linear spaces, systems of linear equations, linear functions of a vector argument, coordinate transformations, the canonical form of the matrix of a linear operator, bilinear and quadratic forms, Euclidean spaces, unitary spaces, quadratic forms in Euclidean and unitary spaces, finite-dimensional space. Problems with hints and answers.

Introduction to Applied Linear Algebra

2018-06-07 Business & Economics
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Release : 2018-06-07
Genre : Business & Economics
Kind : eBook
Book Rating : 965/5 ( reviews)

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Book Synopsis Introduction to Applied Linear Algebra by : Stephen Boyd

Download or read book Introduction to Applied Linear Algebra written by Stephen Boyd. This book was released on 2018-06-07. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

Introduction to Linear Algebra

1993 Mathematics
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Release : 1993
Genre : Mathematics
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Introduction to Linear Algebra by : Gilbert Strang

Download or read book Introduction to Linear Algebra written by Gilbert Strang. This book was released on 1993. Available in PDF, EPUB and Kindle. Book excerpt: Book Description: Gilbert Strang's textbooks have changed the entire approach to learning linear algebra -- away from abstract vector spaces to specific examples of the four fundamental subspaces: the column space and nullspace of A and A'. Introduction to Linear Algebra, Fourth Edition includes challenge problems to complement the review problems that have been highly praised in previous editions. The basic course is followed by seven applications: differential equations, engineering, graph theory, statistics, Fourier methods and the FFT, linear programming, and computer graphics. Thousands of teachers in colleges and universities and now high schools are using this book, which truly explains this crucial subject.

Linear Algebra Done Right

1997-07-18 Mathematics
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Release : 1997-07-18
Genre : Mathematics
Kind : eBook
Book Rating : 595/5 ( reviews)

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Book Synopsis Linear Algebra Done Right by : Sheldon Axler

Download or read book Linear Algebra Done Right written by Sheldon Axler. This book was released on 1997-07-18. Available in PDF, EPUB and Kindle. Book excerpt: This text for a second course in linear algebra, aimed at math majors and graduates, adopts a novel approach by banishing determinants to the end of the book and focusing on understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space has an eigenvalue. The book starts by discussing vector spaces, linear independence, span, basics, and dimension. Students are introduced to inner-product spaces in the first half of the book and shortly thereafter to the finite- dimensional spectral theorem. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition features new chapters on diagonal matrices, on linear functionals and adjoints, and on the spectral theorem; some sections, such as those on self-adjoint and normal operators, have been entirely rewritten; and hundreds of minor improvements have been made throughout the text.

Linear Algebra: Theory, Intuition, Code

2021-02 Mathematics
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Release : 2021-02
Genre : Mathematics
Kind : eBook
Book Rating : 608/5 ( reviews)

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Book Synopsis Linear Algebra: Theory, Intuition, Code by : Mike X. Cohen

Download or read book Linear Algebra: Theory, Intuition, Code written by Mike X. Cohen. This book was released on 2021-02. Available in PDF, EPUB and Kindle. Book excerpt: Linear algebra is perhaps the most important branch of mathematics for computational sciences, including machine learning, AI, data science, statistics, simulations, computer graphics, multivariate analyses, matrix decompositions, signal processing, and so on.The way linear algebra is presented in traditional textbooks is different from how professionals use linear algebra in computers to solve real-world applications in machine learning, data science, statistics, and signal processing. For example, the "determinant" of a matrix is important for linear algebra theory, but should you actually use the determinant in practical applications? The answer may surprise you!If you are interested in learning the mathematical concepts linear algebra and matrix analysis, but also want to apply those concepts to data analyses on computers (e.g., statistics or signal processing), then this book is for you. You'll see all the math concepts implemented in MATLAB and in Python.Unique aspects of this book: - Clear and comprehensible explanations of concepts and theories in linear algebra. - Several distinct explanations of the same ideas, which is a proven technique for learning. - Visualization using graphs, which strengthens the geometric intuition of linear algebra. - Implementations in MATLAB and Python. Com'on, in the real world, you never solve math problems by hand! You need to know how to implement math in software! - Beginner to intermediate topics, including vectors, matrix multiplications, least-squares projections, eigendecomposition, and singular-value decomposition. - Strong focus on modern applications-oriented aspects of linear algebra and matrix analysis. - Intuitive visual explanations of diagonalization, eigenvalues and eigenvectors, and singular value decomposition. - Codes (MATLAB and Python) are provided to help you understand and apply linear algebra concepts on computers. - A combination of hand-solved exercises and more advanced code challenges. Math is not a spectator sport!

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