doc (notebooks): explain feature matrix covariance and PCA

[inati]

We should provide a notebook that describes how to evaluate the covariance of a set of features (say in a training data set) and to inspect the covariance matrix and singular values.

This would be the part of a feature exploration step, maybe leading toward dimensionality reduction, manifold learning, or shiny new things like UMAP