You’ve put in the hard work: you’ve sourced, cleaned and transformed your data, then put some more blood, sweat and tears into analyzing the data and building state-of-the-art models in Python. You’re ready for the world to see the fruits of your labor, but you are not sure how in the world you are actually going to get that done. If this sounds familiar, you’re not alone: only about a tenth of all data science projects ultimately make it to ‘production’.

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