Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Jev AI Will Make You Money – But Exactly How Much?
  Originally published in Forbes As I covered recently, Jev...
Jev Fever: Predictive AI Is Superhot Again
  Originally published in Forbes The more AI changes, the...
GenAI Owns the Hype, but Predictive AI Is Thriving
  EDITOR’S NOTE: This article is adapted from the...
The Data Disconnect: A Key Challenge for Machine Learning Deployment
  EDITOR’S NOTE: This article is excerpted from The...

Original Content

The ML Times Is Growing – A Letter from the New Editor in Chief

  Dear Reader, As of the beginning of January 2020, it’s my great pleasure to join The Machine Learning Times as editor in chief! I’ve taken over the main editorial duties from Eric Siegel, who founded the ML Times (also the founder of the Predictive Analytics World conference series). As you’ve likely noticed, we’ve renamed

Wise Practitioner – Predictive Analytics Interview Series: Dan Steinberg Ph.D. at Salford Systems

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Wise Practitioner – Predictive Analytics Interview Series: Celeste Fralick at McAfee

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Wise Practitioner – Predictive Analytics Interview Series: Jennifer Lewis Priestley at Kennesaw State University

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What Every Analytics Manger Should Know About Working With Universities. But Doesn’t.

   This is part 1 of a 5-part series on university/corporate partnerships in analytics and data science How many .edu addresses do you have in your email contacts? If you are like most Analytics Managers, the answer...

Wise Practitioner – Predictive Analytics Interview Series: Kumaran Ponnambalam at Cisco

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Wise Practitioner – Predictive Analytics Interview Series: Kristen Kehrer at Data Moves Me

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Wise Practitioner – Predictive Analytics Interview Series: Bas Geerdink at Aizonic

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Five Reasons to Go to Machine Learning Week 2020

 When deciding on a machine learning conference, why go to Machine Learning Week 2020? This five-conference event – May 31 – June 4, 2020 at Caesars Palace, Las Vegas – delivers brand-name, cross-industry, vendor-neutral case studies purely...

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...

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