Add a lecture on eigenvals, eigenvectors, Perron-Frobenius and the Neumann series theorem

[mmcky]

Starting point is available in in-work/eigen.md

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@oyamad made a comment

This is not quite true:

A = [[0, 1, 0],
     [0, 0, 1],
     [1, 0, 0]]
np.linalg.eigvals(A)

array([-0.5+0.8660254j, -0.5-0.8660254j,  1. +0.j       ])

A nonnegative matrix has an eigenvalue that is real and attains the maximum absolute value among all eigenvalues (or equivalently, is equal to the spectral radius), and its corresponding eigenvector is (real- and) nonnegative-valued.

@jstac responded

Thanks @oyamad , that was a bad typo!

For context, these lectures are very rough ATM but we will be polishing them this coming week in a code / lecture writing sprint.

The idea is to have a set of lectures that can be taught to undergraduate students.

All further comments are appreciated.

[mmcky]

maanasee

[jstac]

See #94