Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...
Today’s AI Won’t Radically Transform Society, But It’s Already Reshaping Business
 Originally published in Fast Company, Jan 5, 2024. Eric...
A University Curriculum Supplement to Teach a Business Framework for ML Deployment
    In 2023, as a visiting analytics professor...
The AI Playbook: Providing Important Reminders to Data Professionals
 Originally published in DATAVERSITY. This article reviews the new...
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4 years ago
Why Operationalizing Machine Learning Requires a Shrewd Business Perspective

 Originally published in Analytics Magazine For a rocket scientist, the math isn’t the hardest part. What’s hard is being so often misunderstood. The same goes for data scientists, who time and again lack the support needed to successfully launch the fruits of their brilliant labor into action. These math heads have got to integrate into the organization as a whole, lest they vanish into the obscurities of their analysis. Their isolation is an enemy to their usefulness. After all, the most wicked and pervasive pitfall of predictive analytics is organizational in nature, not technical: Predictive models often fail

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