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Came across this yesterday. Can someone (maybe poster?) talk about when you would use this versus something like scikit-learn or any number of R libraries? Is the goal simply to have all machine learning in Java so it can be productionized easier?

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The project homepage says "Data scientists and developers can speak the same language now!". So it is surely easier to producitionize a ML project without rewriting the algorithms after the data scientists work out the model with R or Matlab.

There are more python developers than scala developers. There are more python data scientists than scala data scientists. I like the project, though.

They are more Java developers than python developers :)

I don't know that that's necessarily true. The most recent StackOverflow survey[1] shows a difference of 8%, which is not an overwhelming majority. Granted, that's not an unbiased sample size, but I think the OP above is correct...more data scientists use Python than Java.

So anyone wanting to use this library would have to think about tradeoffs: Are the efficiencies lost in data scientists learning to use Java for modeling worth the efficiencies gained in putting a model in production? For some, the answer may be yes, for some no.

[1]https://stackoverflow.com/insights/survey/2017#technology-pr...

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