This textbook on numerical methods for linear algebra problems presents detailed explanations that beginning students can read on their own, allowing instructors to go beyond lecturing and making it suitable for a “flipped” classroom. The author covers several topics not commonly addressed in related introductory books, including diffusion, a toy model of computed tomography, global positioning systems, the use of eigenvalues in analyzing stability of equilibria, and multigrid methods. A detailed derivation and careful motivation of the QR method for eigenvalues starting from power iteration is also included, as is a discussion of the use of the SVD for grading. Introduction to Numerical Linear Algebra is appropriate for undergraduate and beginning graduate students in mathematics and related fields. It assumes that the reader has taken a course on linear algebra but reviews background as needed. It is intended as a textbook for a one-semester course on numerical linear algebra and provides background and tools for a range of application areas, including data science.

About the Author

Christoph B�rgers is a professor of mathematics at Tufts University. He has worked in and written about several areas of applied mathematics, including numerical methods for elliptic boundary value problems, computational fluid dynamics, computational methods for linear particle transport, computational neuroscience, the mathematics of voting, and anomalous diffusion and L�vy walks. He is the author of two previous books.

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