I have translated into Julia all 45 functions and 160+ examples from my co-authored textbook, Fundamentals of Numerical Computation (SIAM). They cover at an advanced undergraduate level the basics of dense matrix factorizations, rootfinding and nonlinear least-squares, interpolation, initial-value problems, EVD and SVD, Krylov iterations, boundary-value problems, and the method of lines for PDEs.

The Julia codes adopt some of the more important language features, such as comprehensions, but they are largely vanilla transliterations of the original MATLAB codes. They do call on some well-established packages such as `Interpolations`

and `DifferentialEquations`

as complements to the basic algorithms presented. The examples do not include the context from the text but should be typically understandable to experienced computational scientists.

You can find the codes at the Github site for the text.