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Why Do People Say It’s So Hard To Deploy A ML Model To Production?
Aug. 11, 2022, 1:14 p.m. | Tim Liu
Towards Data Science - Medium towardsdatascience.com
Multiple dimensions of change create specialized challenges in ML services
Photo by Dan Lohmar on UnsplashYou’ve heard it said, you’ve heard it written and you’ve heard it sung from the rooftops by analysts and vendors alike: 87% of data science projects never make it into production.
Why is that?
Well, of course, it always depends, but the slightly more precise answer is that building ML services is more complex than building other types of software. While ML applications …
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