I have a bunch of links to ML material for either APL or J. I don't know of any particular library for J. J is interpreted, so it is not as fast as other imple

I have a bunch of links to ML material for either APL or J. I don't know of any particular library for J. J is interpreted, so it is not as fast as other implementations. I am mainly using it to experiment on concepts and teach myself more ML in J because of the iterative nature of the REPL, and the succinct code. I can keep what's going on in my head, and glance at less than 100 lines, usually 15 lines, of code to refresh it. There is a series of videos of learning neural networks in APL cited by others here on this thread. Pandas author, Wes McKinney, cited J as an influence in his work on Pandas. Extreme Learning Machine in J (code and PDF are here too): https://github.com/peportier/jelm https://github.com/peportier/jelm Convolutional neural networks in APL (PDF and video on page): https://dl.acm.org/doi/10.1145/3315454.3329960 https://dl.acm.org/doi/10.1145/3315454.3329960 A DSL to implement MENACE (Matchbox Educable Noughts And Crosses Engine) in APL (Noughts and Crosses or Tic-tac-toe): https://romilly.github.io/o-x-o/an-introduction.html https://romilly.github.io/o-x-o/an-introduction.html