Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Survey: Machine Learning Projects Still Routinely Fail to Deploy
 Originally published in KDnuggets. Eric Siegel highlights the chronic...
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,...

Original Content

Dr. Data Show Video: What the Hell Does “Data Science” Really Mean?

 Watch the latest episode of The Dr. Data Show, which answers the question, “What the hell do data science and big data really mean?” About the Dr. Data Show. This new web series breaks the mold for data science infotainment, captivating the planet with short webisodes that cover the very best of machine learning and

Dr. Data Show Video: How Can You Trust AI?

 Watch the second episode of The Dr. Data Show, which answers the question, “How can you trust artificial intelligence?” About the Dr. Data Show. This new web series breaks the mold for data science infotainment, captivating the...

Three Common Mistakes That Can Derail Your Team’s Predictive Analytics Efforts

  Originally published by Harvard Business Review With today’s high demand for data scientists and the high salaries that they command, it’s often not practical for companies to keep them on staff.  Instead, many organizations work to...

Artificial Intelligence: Are We Effectively Assessing Its Business Value?

 As most data science practitioners know, artificial intelligence (AI) is not new and has been explored by academia back as far back as the fifties. The real core of AI is the branch of mathematics related to...

Dr. Data Show Video: Why Machine Learning Is the Coolest Science

 Watch the premiere episode of The Dr. Data Show, which answers the question, “What makes machine learning the coolest science?” About the Dr. Data Show. This new web series breaks the mold for data science infotainment, captivating...

Blatantly Discriminatory Machines: When Algorithms Explicitly Penalize

 Originally published in The San Francisco Chronicle (the cover article of Sunday’s “Insight” section) What if the data tells you to be racist? Without the right precautions, machine learning — the technology that drives risk-assessment in law...

Data Reliability and Validity, Redux: Do Your CIO and Data Curators Really Understand the Concepts?

 Here are two recent entries on the big but neglected issue of data reliability and analytic validity (DR&AV), from the vast commentariat that is LinkedIn: One of my complaints with hashtag#bigdata, is there isn’t enough focus on...

On Variable Importance in Logistic Regression

 The model looks good. It’s parsimonious, provides effective segmentation, and the predictors appear to be intuitively reasonable. While there is no problem with deploying results, you need to be able to order the variables in terms of...

Data-Driven Decisions for Law Enforcement in Toronto

 For today’s leading deep learning methods and technology, attend the conference and training workshops at Predictive Analytics World for Government, Sept 17-21, 2018 in Washington, DC. Data-driven decisions for law enforcement are not new and have been used...

AI, Machine Learning, and the Basics of Predictive Analytics for Process Management

 APQC Chair Carla O’Dell interviews Predictive Analytics Times Executive Editor and Predictive Analytics World Founder Eric Siegel about predictive analytics and machine learning’s application to process management. Dr. Siegel will be speaking at APQC’s Process & Performance...

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