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If I wanted to do ML but with lispy syntax I'd probably use Hy, which is just a python re-skin. There is plenty of literature out there about ML in Hy (although it's not hard to translate from python too).

For example: https://github.com/FPTensorFlow/hy-tensorflow-tutorials

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I prefer https://github.com/gilch/hissp, where Hy has to use shims to pretend statements are expressions, Hissp just targets the expression subset in the first place. (though as you mentioned, hy has a lot of literature and support around it, where as you're going to have to find your own way around hissp)

You don't have to go it alone. Hissp does have documentation (which is pretty thorough) if you want to try, but there's also a community chat on Gitter/Matrix: https://gitter.im/hissp-lang/community

If you know how to do it in Python (or Hy, probably) the community chat can help show you how to translate it to Lissp.

The Lissp REPL also shows the Python compilation before evaluating it, so if you're already familiar with Python, that can help you get a handle on Hissp.

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