Darve E., Wootters M. Numerical Linear Algebra with Julia 2021

Textbook in PDF format

Numerical Linear Algebra with Julia provides in-depth coverage of fundamental topics in numerical linear algebra, including how to solve dense and sparse linear systems, compute QR factorizations, compute the eigendecomposition of a matrix, and solve linear systems using iterative methods such as conjugate gradient. Julia code is provided to illustrate concepts and allow readers to explore methods on their own.
Getting started with Julia
Linear algebra bootcamp
Linear systems and the basics of floatingpoint arithmetic
OR factorization
Eigenvalues and eigenvectors
Eigenvalue computation for sparse matrices
Classical iterations to solve linear systems
Krylov methods to solve linear systems
A taste of direct methods to solve sparse linear systems
Julia essentials
Bibliography
Index