
Machine learning (ML) can provide unique analytical insights, as well as help automate some operational and decision-making processes more efficiently and effectively than non-ML alternatives. However, ML is also among the buzziest of buzzwords, and many are overselling and oversimplifying its usage. Do not let anyone frame a data analysis, business problem, or process improvement as an ML use case. Instead, say: That is Not Machine Learning — that is a data analysis, business problem, or process improvement where ML might be able to help. But not before we evaluate other options. And with the understanding that ML is rarely going to be either the first or only aspect of the solution. This episode is sponsored by: Vertica.com Extended Show Notes: ocdqblog.com/dbp Follow Jim Harris on Twitter: @ocdqblog Email Jim Harris: ocdqblog.com/contact Other ways to listen: bit.ly/listen-dbp
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