Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Survey: Machine Learning Projects Still Routinely Fail to Deploy
 Originally published in KDnuggets. Eric Siegel highlights the chronic...
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,...
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6 years ago
Data Reliability and Validity, Redux: Do Your CIO and Data Curators Really Understand the Concepts?

 Here are two recent entries on the big but neglected issue of data reliability and analytic validity (DR&AV), from the vast commentariat that is LinkedIn: One of my complaints with hashtag#bigdata, is there isn’t enough focus on getting the right kind of data. We deal with this in healthcare all the time. Much of our transactional data is just outcomes. There’s a push in the industry to change health behaviors (generally: population health). But if we’re not collecting meaningful behavioral data (could be secondary data like credit card purchases or primary like surveys about health attitudes), we can’t

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