Skip wrote:
>Recently, R & Python have developed fairly extensive Machine Learning
libraries in those languages.
>If you want to promote J, you need to show how J solves problems in a hot
>field like AI, better, faster, or more concisely than other languages.
That
>is essentially how Octave/Matlab ​got thousands of students learning the
>language. I was tempted to try to code some of my ML homework assignments
>in J, but the time pressure of the weekly assignments as well as other
>obligations, prevented that exercise.
FWIIW, I am working on a few machine learning doodads for J. Though I
have been doing Octave/matlab for 20 years, and R for 10, and J for only
a little while (and only on a part time basis), when I want to learn a
new technique in detail, I code it in J. It's really living up to its
reputation as a notation and a tool for thought. My code isn't very
dense, since I'm still a beginner, but it's always more clear and less
wordy than equivalent R or Matlab.
It is a shame it isn't being used in ML research. My R&D work has
recently brought me in contact with the deep learning environment
Torch7. There is no reason that couldn't have been written in J rather
than Lua, and life would be a heck of a lot nicer if it was. It might
not be too bad pulling CUBLAS into J via the FFI (Torch7 and Theano do
this: the GPU is much faster on neural problems), though it would be
tough figuring out how to turn these BLAS into J primitives.
-SL
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