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...

Original Content

Customer Experience Predictions for 2016

 As we look ahead and see 2016 unfurling in front of us, the team at Beyond the Arc wanted to play the role of #stylespotter. What’s the “new black” for companies focused on improving customer experience? We’re happy to share some of our prognostications. In 2016, companies will discover the power of simplicity to build

Predictive Analytics Book Excerpt: Hands-On Guide—Resources for Further Learning

 Here is the Hands-On Guide that appears at the end the Revised and Updated paperback edition of Eric Siegel’s Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Although the book Predictive Analytics...

Wise Practitioner – Predictive Analytics Interview Series: Hans Wolters at Microsoft

 In anticipation of his upcoming conference presentation, Predicting User and Device Upgrade Issues Moving to Windows as a Service, at Predictive Analytics World San Francisco, April 3-7, 2016, we asked Hans Wolters, Principal Data Scientist, Windows and...

Machine Learning: Not Necessarily a New Phenomenon in Predictive Analytics

 One of the more recent topics gaining traction in Big Data Analytics is the notion of machine learning. Many people think that this is a recent development or phenomenon occurring as a result of newer Big Data...

Wise Practitioner – Predictive Workforce Analytics Interview Series: Frank Fiorille at Paychex, Inc.

 In anticipation of his upcoming Predictive Analytics World for Workforce conference presentation, Balancing Privacy with Powerful Employee Churn Predictions, we interviewed Frank Fiorille, Senior Director of Risk Management at Paychex, Inc. View the Q-and-A below to see how Frank Fiorille has...

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 Case Against Quick Wins in Predictive Analytics Projects

 When beginning a new predictive analytics project, the client often mentions the importance of a “quick win”. It makes sense to think about delivering fast results, in a limited area, that excites important stakeholders and gains support...

Wise Practitioner – Predictive Workforce Analytics Interview Series: Jason Noriega at Chevron

 In anticipation of his upcoming Predictive Analytics World for Workforce conference co-presentation, Open Sourced Workforce Analytics: An Overview of 3 Algorithms for Common Predictive Modeling Situations, we interviewed Jason Noriega, Diversity Analytics Team Lead at Chevron. View the Q-and-A below to...

Wise Practitioner – Predictive Analytics Interview Series: Matthew Pietrzykowski at General Electric

 In anticipation of his upcoming conference co- presentation, Advanced Analytics and the Corporate Audit Function at Predictive Analytics World San Francisco, April 3-7, 2016, we asked Matthew Pietrzykowski, Senior Data Scientist at General Electric, a few questions about...

B2B Predictive Analytics: An Untapped Sector

 Much work in predictive analytics and data science has been primarily focused around the business to consumer sector (B2C). Certainly predictive analytics solutions have been applied to the B2B sector but it pales in comparison to what...

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