About this ebook
This book presents a comprehensive and modern treatment of matrix theory, progressing from foundational concepts to advanced applications in science, engineering, economics, data science, and machine learning. Designed with clarity and rigor, it combines theoretical explanations with step-by-step numerical examples, real-world applications, and computational perspectives.
Beginning with the basics of matrices, operations, and systems of linear equations, the text advances through vector spaces, linear transformations, eigenvalues, orthogonality, and matrix decompositions. The final chapters address contemporary applications, including differential equations, numerical methods, data science, machine learning, and computational tools such as MATLAB and Python.
This book is suitable for undergraduate and postgraduate students, instructors, researchers, and professionals who require a solid and practical understanding of matrices. It can be used as a core textbook, a supplementary reference, or a self-study guide.
This book presents a comprehensive and modern treatment of matrix theory, progressing from foundational concepts to advanced applications in science, engineering, economics, data science, and machine learning. Designed with clarity and rigor, it combines theoretical explanations with step-by-step...
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