Machine Learning Times
Machine Learning Times
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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
Wise Practitioner – Predictive Analytics Interview Series: Richard Lee at John Hancock Financial

 In anticipation of his upcoming conference presentation, Detecting Incorrect Payments: The Payment Defect Model, at Predictive Analytics World for Financial in Las Vegas, June 3-7, 2018, we asked Richard Lee, Manager of Operations Reporting Consistency at John Hancock Financial, a few questions about his work in predictive analytics. Q: In your work with predictive analytics, what behavior or outcome do your models predict? A: Most of the work I do is geared towards needle in the haystack type of problems. These are the most interesting cases as overall accuracy is moot point due to the nature of the data. In

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