Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
How Predictive AI Will Solve GenAI’s Deadly Reliability Problem
  Originally published in Forbes Generative AI too unreliable to...
5 Ways To Hybridize Predictive AI And Generative AI
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This Simple Arithmetic Can Optimize Your Main Business Operations
 Originally published in Forbes Deep down, we all know that...
Predictive AI Usually Fails Because It’s Not Usually Valuated
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By: Dean Abbott, President, Abbott Analytics 

 The Cross Industry Standard Process for Data Mining (CRISP-DM) is the leading published methodology for Data Mining (DM), and by extension, Predictive Analytics (PA). I use it routinely as I lead PA projects and when I teach appiled DM and PA courses. It was the subject of three KD-Nuggets polls, in 2002, 2004, and 2007) and nearly half of the responders stated they used it as the main methodology for DM (http://www.kdnuggets.com/polls/2007/data_mining_methodology.htm). There are six stages in the CRISP-DM process, including Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation and Deployment. There are many excellent books describing five

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