Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Incoherent AGI Hype Spurs An Industrywide Pivot To Hybrid AI
  Originally published in Forbes Recently on The Dr. Data Show,...
The AI Paradox: More Humanlike Means Less Autonomous
  Originally published in Forbes The AI executives are at...
How To Overcome The Confidence-Killer That Destroys Most Predictive AI Projects
  Originally published in Forbes When Henry Castellanos first presented...
You Must Address These 4 Concerns To Deploy Predictive AI
 Originally published in Forbes Most predictive AI projects fail to launch into production. The...
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By: Dr. John Elder, CEO & Founder, Elder Research, Inc

 (Part 3 of 11 of the Top 10 Data Mining Mistakes, drawn from the Handbook of Statistical Analysis and Data Mining Applications) -John Elder (elder [at] datamininglab [dot] com) “To a little boy with a hammer, all the world’s a nail.” All of us have had colleagues (at least) for whom the best solution for a problem happens to be the type of analysis in which they are most skilled! For many reasons, most researchers and practitioners focus too narrowly on one type of modeling technique. But, for best results, one needs a whole toolkit. At the very

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