April 2020
Intermediate to advanced
192 pages
2h 28m
English
by Cassie Kozyrkov
The top trophy hire in data science is elusive, and that should be no surprise: A “full-stack” data scientist has mastery of machine learning, statistics, and analytics. When teams can’t get their hands on a three-in-one polymath, they set their sights on luring the most impressive prize among the single-origin specialists. Which of those skills gets the podium?
Today’s fashion in data science favors flashy sophistication with a dash of sci-fi, making AI and machine learning the darlings of the job market. Alternative challengers for the alpha spot come from statistics, thanks to a century-long reputation for rigor and mathematical superiority. What about analytics?
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