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The reality is that most of a modelling task is preprocessing your data before it can be passed to a probabilistic model and postprocessing to make decisions using it. The code is usually written in R or Python so there is a strong pressure for your library to be in that language as well.

And being rough around the edges is an ok price to pay for not losing an ecosystem.




My take is that most modern PPLs have language bindings in JavaScript/Python/R because they are explicitly courting analysts/data-scientists/applied-statisticians, or they are taking advantage of modern technical stacks implementing auto-diff and co-processor routines.

Most pre- and post- processing (with the exception of visualization) should probably be a part of your model!




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