Machine Learning Times
EXCLUSIVE HIGHLIGHTS
The Data Disconnect: A Key Challenge for Machine Learning Deployment
  EDITOR’S NOTE: This article is excerpted from The...
A Brief History of Why Machine Learning Projects Stall
  EDITOR’S NOTE: This is the preface to The...
Hybrid AI Emerges To Tame LLMs – And Not A Moment Too Soon
 Originally published in Forbes The great potential of LLMs is...
AGI Is Infeasible. Instead, Pursue Superhuman Adaptable Intelligence
  Originally published in Forbes On a recent episode of the...

Original Content

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 technologies. But think about the phrase “machine learning”. Essentially, the computer “learns” based on what the user or

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...

Wise Practitioner – Predictive Workforce Analytics Interview Series: Greg Tanaka at Percolata

 In anticipation of his upcoming Predictive Analytics World for Workforce conference presentation, Big Data Driven Labor Scheduling, we interviewed Greg Tanaka, CEO at Percolata. View the Q-and-A below to see how Greg Tanaka has incorporated predictive analytics into the workforce...

Wise Practitioner – Predictive Workforce Analytics Interview Series: Michael Li at The Data Incubator

 In anticipation of his upcoming Predictive Analytics World for Workforce conference presentation, Finding Top Data Scientists for Your Organization: Optimize the Hiring Process with Analytics, we interviewed Michael Li, CEO at The Data Incubator.  View the Q-and-A below to see...

Four Ways Data Science Goes Wrong and How Test-Driven Data Analysis Can Help

 If, as Niels Bohr maintained, an expert is a person who has made all the mistakes that can be made in a narrow field, we consider ourselves expert data scientists.  After twenty years of doing what’s been...

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