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...

Elder Research

Why Do We Stop Asking Why?

 I’ve lived through this phenomenon first hand. The environment was new to me, sitting at my assigned seat at the cherry wood conference table for the weekly executive staff meeting. I was told very clearly that I was to stick to the presentation, answer only when asked a direct question, and never, no matter what

Netflix, Dark Knowledge, and Why Simpler Can Be Better

 Weary from an all-night coding effort, and rushed by the looming 6:42PM deadline, Lester Mackey searched franticly for the proper prediction file to submit. Lester was a member of “The Ensemble”—a large coalition of data scientists who...

The Quest for Unicorns

 Will there be enough data scientists in the future? The question sounds like a subplot for a science fiction film, but it has received much attention over the past few years due to the forecast of a...

Good Predictions != Good Decisions

 A Fateful Tale Ted is having a rough week at work. As a call-center employee, his main focus is on customer retention and offering promotions to his company’s current subscribers. For some reason, his numbers are horrible...

Empathy and Data Science: A Fable of Near-Success

 Editor’s Note: While the story is fiction, the events are drawn from the experiences of the author and his colleagues. Michael is an analytics director. This evening we find him frazzled. As he pulls out of the...

Defensive Data Science: What we can Learn from Software Engineers

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Space Alien Eager to Convey Thoughts on Data Science

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From Code to Reports with knitr & Markdown

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Visualizations Get Some Snap from R Shiny

 “Numbers have an important story to tell. They rely on you to give them a clear and convincing voice.” –Stephen Few Every data scientist bears the burden of clearly and convincingly communicating results to a client or...

Top 10 Data Mining Mistakes

 Dr. Elder gives his famous talk on the Top Ten Data Mining Mistakes. The Top Ten Mistakes are covered in chapter 20 of the Handbook of Statistical Analysis & Data Mining Applications. You can also view this...

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