I read the Klong book [0] and for me it "clicked" in a way that J/K never had. The author did a really nice job paring down the language and cleaning up some of the ambiguities in a way that made it approachable. Also, after reading it I've found APL and J more approachable, which is encouraging.
If you'll forgive the style, I took a swing at implementing k-means clustering in Klong a few months ago [1]. While I did find a few slow-downs with a modestly sized data set (Fisher's iris data), I think Klong is built on a Forth-like VM using the core of a scheme implementation (all of which the author wrote!). It wasn't slow enough to really bother me, as I was more interested in learning about array languages and algorithms.
If you'll forgive the style, I took a swing at implementing k-means clustering in Klong a few months ago [1]. While I did find a few slow-downs with a modestly sized data set (Fisher's iris data), I think Klong is built on a Forth-like VM using the core of a scheme implementation (all of which the author wrote!). It wasn't slow enough to really bother me, as I was more interested in learning about array languages and algorithms.
I'm a fan of Klong -- it's just fun.
[0]: http://www.t3x.org/klong/book.html
[1]: https://idle.nprescott.com/2019/k-means-clustering-in-klong....