Machine Learning Times
Machine Learning Times
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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
Machine Learning Tip: Nested Cross Validation – When (Simple) Cross Validation Isn’t Enough

 Several scientific disciplines have been rocked by a crisis of reproducibility in recent years [1]. Not long ago, Bayer researchers found that they were only able to replicate 25% of the important pharmaceutical papers they examined [2], and an MIT report on Machine Learning papers found similar results. Some fields have begun to emerge from their crises, but other fields, such as psychology, may have not yet hit bottom [3] [4]. We might imagine that this is because many scientists are good at science but not so adept with statistics. We might even imagine that we Analytics practitioners should have fewer problems

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