Original Content
By: Sam Koslowsky, Harte Hanks
Data miners employ a variety of techniques to develop robust predictive models. Often, our analysts are confronted with a dilemma. Should we construct one model to address the business objective? Or perhaps, multiple models may be in order? Take, for example, a marketer that has a presence on the east coast and in the mid-west.
This commentary first appeared in the San Francisco Chronicle. Originally published as the cover piece for the Insight commentary section in the Sunday San Francisco Chronicle, this op-ed by Eric Siegel points out that, although many believe...
In anticipation of his upcoming conference presentation, The Sprint for Teaching Data Science: LinkedIn Learning, Analytics and the New Era of Just-In-Time Skills Training at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we...
In anticipation of her upcoming conference presentation, Which Predictive Model Will Best Help Increase Retention? at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we asked Emilie Lavoie-Charland, Research & Innovation Analyst at The...
By Seth Stephens-Davidowitz
This author will present at Predictive Analytics World, Oct 29 – Nov 2 in New York. This article is excerpted from his book, Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are....
As I have stated in previous articles, the most difficult challenge in building predictive models is the creation of the analytical file. Typically, this comprises between 80%-90% of the data scientist’s time with 10%-20% comprising the actual...
Greta Roberts, CEO Talent Analytics, Corp.
Talent Analytics uses data gathered from our own proprietary talent assessments as an input variable to predict hiring success – pre-hire. We treat this dataset just like any other dataset in our predictive work. We are careful...
In anticipation of her upcoming conference presentation, Crowd-Sourcing and Quality: How To Get The Best Out of Hand-Tagged Training Data for Machine Learning Models at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we...
From the perspective of data science, a Muslim ban would weaken security, not strengthen it (click for additional articles by Eric Siegel on analytics and social justice). Originally published by Scientific American June 14, 2017 Let’s not...
In anticipation of his upcoming conference presentation, Regulating Opacity: Solving for the Conflict Between Laws and Analytics at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we asked Andrew Burt, Chief Privacy Officer &...
