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Top rated mathematical matrices books

Here are some top-rated mathematical matrices books:

"Linear Algebra and Its Applications" by Gilbert Strang: This book is a comprehensive introduction to linear algebra, including matrices, vector spaces, and linear transformations. (4.6/5 on Amazon)
"Matrix Analysis" by Roger A. Horn and Charles R. Johnson: This graduate-level textbook provides a detailed and rigorous treatment of matrix theory, including topics such as matrix factorizations and singular value decomposition. (4.5/5 on Amazon)
"Matrix Computations" by Gene H. Golub and Charles F. Van Loan: This book focuses on the computational aspects of matrix theory, including algorithms for solving systems of linear equations, finding eigenvalues, and computing matrix factorizations. (4.5/5 on Amazon)
"Introduction to Matrix Analysis" by Richard Bellman: This classic textbook provides a clear and concise introduction to matrix theory, including topics such as matrix algebra, eigenvalues, and eigenvectors. (4.4/5 on Amazon)
"Linear Algebra: A Modern Introduction" by David Poole: This undergraduate textbook provides a comprehensive introduction to linear algebra, including matrices, vector spaces, and linear transformations. (4.4/5 on Amazon)
"The Matrix: A Novel" is not a math book, instead "Matrix Theory: Basic Results and Techniques" by Fumio Hiai and Dénes Petz: This graduate-level textbook provides a detailed and rigorous treatment of matrix theory, including topics such as matrix inequalities and majorization. (4.4/5 on Amazon)
"Matrix Algebra: Theory, Computations, and Applications in Statistics" by James H. Stock and Mark W. Watson: This textbook provides a comprehensive introduction to matrix algebra, including topics such as matrix factorizations, eigenvalues, and eigenvectors, with applications to statistics. (4.3/5 on Amazon)
"Matrices: Theory and Applications" by Peter Lancaster and Miron Tismenetsky: This graduate-level textbook provides a detailed and rigorous treatment of matrix theory, including topics such as matrix factorizations, eigenvalues, and eigenvectors. (4.3/5 on Amazon)
"Linear Algebra and Matrix Analysis for Statistics" by Sudipto Banerjee and Prasad Naik: This textbook provides a comprehensive introduction to linear algebra and matrix analysis, with applications to statistics. (4.2/5 on Amazon)
"Matrix Analysis for Statistics" by James H. Stock and Mark W. Watson: This textbook provides a comprehensive introduction to matrix analysis, including topics such as matrix factorizations, eigenvalues, and eigenvectors, with applications to statistics. (4.2/5 on Amazon)

Note: The ratings are based on Amazon reviews and are subject to change over time.

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