A 91%-accurate predictive maintenance model built in four months sits unused six months later. The problem wasn't the algorithmโit was missing pipelines, documentation, and ownership. Enterprise ML stalls not because science fails, but because infrastructure and operations do.
Originally published on David Ohnstad
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