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I should like to know if Nim can be used for machine learning or for deep learning. How could be located Nim in comparison to Julia, numpy, Torch7 and the tools for deep learning and AI that many big companies are open sourcing.

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I think Nim would be ideal for that kind of applications, in particular neural networks stuff. But definitely we are not there yet. I try to explain my reasons in this blog post: http://rnduja.github.io/2015/10/21/scientific-nim/

To get to a point where we have something good to use, though, there are a few libraries to develop. I started working out a basic layer for linear algebra, that is needed in many applications - see http://unicredit.github.io/linear-algebra/

I hoped I would be able to start working on some neural network stuff based on that, but I did not find the time yet...

Interesting post. I also enjoyed the posts about Torch but when installing in ubuntu 15.10 there were some problems. Libraries are necessary to avoid reinventing the wheel.

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