I'm deciding between Common Lisp and Mojo, so maybe I will try to implement this in Mojo and compare. Anybody have any thoughts on this, since I am a mediocre Lisper and a beginning Mojo person. I am familiar with Numpy and I also program in APL and J.
May I suggest Julia? Efficient and capable of (Common Lisp style) abstractions. Unsurprisingly, there are more than a few quantum projects in the ecosystem already.
I've used Julia with Pluto and Weave to create engineering calculations and reports when I was working at an engineering company, but I want something more general purpose. I've used CL for little scripts and utilities with Portacle, and I find I am more comfortable with the Lisp way of doing things. I had used Mathlab before, so Julia's syntax is very familiar. I do like the Models.jl library.
Don't fret if you think you're mediocre. I myself have been trying to get through On Lisp since 2008. Then, after that, Let over Lambda. Not better, but v strong book, i can tell the guy while not the best at humblebragging has so much cool stuff there.
ANSI Common Lisp n that's plenty to not be mediocre! I did get through the whole thing in 2009, what a great book!
Thanks for the motivation. I love Lisp, and even was into Shen[0] for a while, but Common Lisp has all the libraries and legacy tutorials and books that I will stick it out a bit more. Which matrix/math libraries do you recommend to compete with the likes of Numpy and Mojo for ML apps? Because I love APL, April, Array Programming Re-Imagined in Lisp[1].
