Implement matrix inverse from scratch

[convoliution]

Right now in linalg.py, I'm using numpy.linalg.inv() for matrix inverses. I'd like to implement it from scratch instead, but it looks rather difficult...

Cholesky decomposition looks tractable, see:

• https://rosettacode.org/wiki/Cholesky_decomposition#Python3.X_version_using_extra_Python_idioms

[convoliution]

Note that Cholesky decomposition is only applicable to Hermitian matrices, which will work for PCA but hopefully I can also implement a more general-case algorithm like LUP decomposition as a fallback

[convoliution]

How to compute a matrix inverse using Cholesky decomposition

Back- and forward substitution