Thanks for the notes, they look interesting. The Jacobi algorithm coded in Julia by someone competent is also very welcome - I heard it's perfect for tracking the evolution of eigenvalues when a matrix is continuously transformed, but I was too lazy to implement it myself! Probably a dedicated package might be useful to more people.
> The lecture notes are all Jupyter notebooks, see > https://github.com/ivanslapnicar/GIAN-Applied-NLA-Course > > Any feedback is welcome! >
