The e-retailer reports a $126 million net loss, stemming from a $640 million year-over-year increase in spending in the quarter on technology and content ...
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"We did not invent a new algorithm; we merely use data analysis in a different way. Traditional predictive modeling is a much more time-intensive endeavor, and is nowhere near as flexible as the approach that we have created. We can test 100 different predictive models in one second and then remove 80-90 percent of those noisy or correlated variables," said Dr. Sayad. "The real-time learning that is deployed in our system creates massive spikes on top of an existing lift in positive targeting, and this is the breakthrough that has produced the success that we are seeing in campaigns that have used this system."
About Dr. Saed Sayad
A pioneering researcher in real-time data mining and big data analysis, Dr. Sayad has designed, developed and deployed many business and scientific applications of predictive modeling. The author of ‘An Introduction to Data Mining,' Dr. Sayad teaches a popular graduate course in data mining at the University of Toronto, where is an adjunct professor.
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