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Photo by Nick van den Berg on Unsplash

We live in a world where complex predictions can often be expressed with a single number. Banks use FICO scores as being predictive of whether you will repay a loan on time. Universities use SAT scores as (supposedly) being predictive of how you will do in college. Nightclub owners use a band’s social media numbers as indicative of whether they should book the band (seriously).

Peter Lufkin, a data scientist in Santa Barbara, has developed a system to predict the condition of real estate property without a physical inspection. If you’re looking at buying a house somewhere you can look up its predicted selling price using a site such a Zillow, but there’s no way to know its condition and potential deferred maintenance without sending a contractor out for a physical inspection. …


Bret Waters

Stanford • 4thly • Miller Center

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