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,...

Richard Boire

Predicting Fraud: Another Not So Easy Task

 As I have stated in previous articles, the most difficult challenge in building predictive models is the creation of the analytical file. Typically, this comprises between 80%-90% of the data scientist’s time with 10%-20%  comprising the actual run or runs of the different mathematical/statistical algorithms. In the creation of the analytical file, the two elements

Automation and its impact on Predictive Analytics-Creating the Analytical File

 In my last article, I discussed the increasing impact of automation on business and the displacement of jobs. With artificial intelligence looming as the ultimate disruptor, the overall theme of job displacement has shifted more towards knowledge-intensive...

Artificial Intelligence, Automation, and Predictive Analytics (Part 1)

 Artificial intelligence seems to be the latest term which is capturing the not only the predictive analytics discipline’s attention but the general public as well as seen by the many articles in much of the mainstream media....

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