Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...

data mining

Text Analytics: ROI Recipe Secret Ingredient

 Vendors, the trade press and even popular media are talking about the world’s rapidly expanding body of electronic data. Lots of data equals lots of value, right? The not-so-subtle message surrounding all this is that data is the new gold rush, so you’d better get your stake in the game now. Often, the data is

The Big Risks of Big Data Mining

 “Every step you take, I’ll be watching you” – when Sting wrote those lyrics back in the ’80’s he most certainly wasn’t thinking about digital data collection. But whether we realize it or not, every digital step...

Data Mining Reveals How Human Health Varies with City Size

 If you live in a big city, you are more likely to catch flu but less likely to die of a heart attack or be diagnosed with diabetes, say public health scientists. The science of allometry, the...

The Key to Modelling Success -The Variable Selection Process (Part 1)

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Overstatement of Results in Predictive Analytics

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Tell Your Kids to be Data Scientists, Not Doctors

 Recently I had the pleasure of being interviewed by John Phillips at CNBC about our data scientist salary study. His article, Why Your Kids Will Want to be Data Scientists, was published at the end of May, and...

As talent war intensifies, recruiters turn to analytics

 Baseball scouts used to scour the back roads of America in search of the next Mickey Mantle or Warren Spahn. Today, team front offices rely on reams of statistics and psychological profiles that help predict not only...

Q&A with Data and Analytics Expert Dean Abbott

 Data scientist Dean Abbott has been focusing on data mining and predictive analytics for more than 25 years, and has authored and co-authored several books including “Applied Predictive Analytics,” “IBM SPSS Modeler Cookbook” and contributed a biographical...

Data Mining Group Updates PMML

 Version 4.2 of the Predictive Model Markup Language (PMML), which aims to make it easier to develop predictive analytics apps, is now available. The Data Mining Group, a vendor-led consortium of companies and organizations developing standards for...

Top 10 Data Mining Mistakes

 Dr. Elder gives his famous talk on the Top Ten Data Mining Mistakes. The Top Ten Mistakes are covered in chapter 20 of the Handbook of Statistical Analysis & Data Mining Applications. You can also view this...

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