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awesome-cl#machine-learning mentions clml and mgl; have you tried them*?
awesome-cl#machine-learning mentions clml and mgl; have you tried them*?
If you can structure your code so that data de/serialization is not a bottleneck, then you could access the python libraries using py4cl/2.
If you can structure your code so that data de/serialization is not a bottleneck, then you could access the python libraries using py4cl/2.
*I have not; I have a couple of WIP/alpha-stage libraries like dense-arrays and numericals that could be useful; once I find the time, I want to think about if these or its dependencies can be integrated into the existing libraries including antik mentioned by awesome-cl.
*I have not; I have a couple of WIP/alpha-stage libraries like dense-arrays and numericals that could be useful; once I find the time, I want to think about if these or its dependencies can be integrated into the existing libraries including antik mentioned by awesome-cl.
TH has a cats and dogs example.
Depending on what features of lisp you are looking for, you might find julia to be useful. I personally dislike JIT because I want compile to mean compile, and in the absence of super-fast JIT, the waiting time on every small update seems to break my flow-state. And there are many other things that SBCL and Common Lisp in general provide that are still lacking.