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Monday, September 14, 2020

Data Science Fails If it Looks too Good to be True

Not sure if I completely agree.  Have seen very good results come out of an analytic solution.  I agree that if it makes recommendations very different from current practice, or suggests buying into high risk, depends on unknown future states or or high investments, it deserves very close examination.    But if it simply has different methods, results or valuation.  Why not?  Hype bothers me too, but much value started there.

DSC Podcast

Data Science Fails – If It Looks Too Good To Be True...

You’ve probably seen amazing AI news headlines such as: AI can predict earthquakes. Using just a single heartbeat, an AI achieved 100% accuracy predicting congestive heart failure. AI can diagnose covid19 in seconds from a chest scan. A new marketing model is promising to increase the response rate tenfold. It all seems too good to be true. But as the modern proverb says, “If it seems too good to be true, it probably is”.

In this latest Data Science Central podcast, https://dsc.news/3fhbOt9  we look behind the hype to show whether there is substance to these claims, and then show you how to avoid these types of data science fails.
Speaker: Colin Priest, VP of AI Strategy - DataRobot
Hosted by: Sean Welch, Host and Producer - Data Science Central

via DataRobot

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