Cassie Kozyrkov, Head of Decision Intelligence at Google, outlines how the history—and exciting future—of machine learning is all about our relationship with data sets paid intel
This is why machine learning is a revolution of data sets, not just data. It depends on the luxury of having enough data for a three-way split.
With this puzzle piece in place, we have the full complement of professions: ML/AI, analytics and statistics. The umbrella term that encompasses all of them is calledModern data science is the product of our three-data set era, but many industries routinely generate more than enough data. So is there a case for four data sets?
By subjecting your validation data set to analytics, you’re effectively turning your three data sets back into two. Instead of finding help, you’ve unwittingly gone back an era!
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