Predictive Analytics

The culprit that kills learning is overlearning (aka overfitting). Overlearning is the pitfall of mistaking noise for information, assuming too much about what has been shown within data. You’ve

is a good idea, persuasion modeling determines whether contact is a better idea than not contacting.

YouTube gains an hour of video each second. Estimates put the World Wide Web at over 8.32 billion web pages.

“Who is leaving but would stay if we contacted them?” This sounds pretty convoluted.

Must souping up model precision involve overwhelming complexity, or is there an elegant way to build and scale?

A McKinsey report states, “By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5

Predictive model—A mechanism that predicts a behavior of an individual, such as click, buy, lie, or die (or prepay a mortgage). It takes characteristics (variables) of the individual as input, and provides a predictive score as output. The higher the score, the more likely it is that the individual will exhibit the predicted behavior.

Unlike the social sciences, PA’s objective is to improve operational efficiency rather than figure people out for its own sake—and, either way, just because you’re observing a person does not mean that person is being treated like an animal.

Alexis Madrigal, senior editor at The Atlantic, points out that a user’s data can be purchased for about half a cent, but the average user’s value to the Internet advertising ecosystem is estimated at $1,200 per year.