I think the audience is more the quantitative "data science"/ machine learning crowd.

The nice friendly web design makes this look deceptively simple (and it is if you have the right background), but this type of material is not aimed at a general audience.

At the same time, as noted by another commenter, this isn't arXiv material either.

It's somewhere in between.

I think it's a recruiting tool, so they are okay if only the jargon is indecipherable by most readers. In fact, it's probably signalling to their targets that they are serious about machine learning.

I found it enjoyable and understandable, but I guess I was already slightly familiar with matrix factorization for recommendation/characterization problems.