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Presumably this will usually be run from a JS engine like Node independent of a browser. Which will have all the libraries needed for loading data and such. In theory it will be an order of magnitude faster than numpy because it uses the GPU (I don't know what the actual performance is though.) Certainly the JS will be much faster than python or R.

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Deeplearn.js is designed for webGL on a browser. I'm not sure if it'll work in Node. And on a server you'd probably want to target OpenCL.

Node adds file support, but libraries for stuff like dataframes are still in their early days. That might not be a problem for example problems, but real world data needs cleaning up before you can start doing ML.

It doesn't work in node yet, a relevant issue: https://github.com/PAIR-code/deeplearnjs/issues/234

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