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...
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7 years ago
Automation and Its Impact on Predictive Analytics – The Increasing Importance of the Hybrid-Part 3

 In my last article, I discussed the increasing impact of automation and its actual impact in creating the analytical file. As any data scientist knows, this component or stage of the data science process can typically represent well over 80% of actual project time with 90% not too being too atypical. With artificial intelligence (AI) looming as the ultimate disruptor, the overall theme of job displacement has shifted more towards knowledge-intensive jobs which would of course include data scientists.  The article ended on the note that this article would look at the future of the data scientist in

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