contribution: scikit-learn style machine learning estimators?
Hi All (& @bluenote10 / @mratsim specifically),

I just started looking into Nim more seriously, and this project really caught my eye. So to start, I wanted to say nice work so far :)

I was curious as to whether or not the maintainers would be open to contributions of scikit-learn style estimators? It seems like there is a lot of room for arraymancer to grow. At first, I considered making a separate repo, since arraymancer seemed more akin to numpy than scikit-learn, and there is value in separation. However, after looking through more examples (e.g. PCA, or a least squares solver) I figured I shouldn't make so many assumptions, and that it might make more sense to add to this repo directly rather than making a separate project?

So, to summarize, is there openness or willingness to expand this library to support higher level and varied machine learning estimators similar to those in torch/scikit-learn/spark specifically in this repo? Or would a separate repo/project be better?

Best,
Xander