Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Guidebook to the Future of Data Science: How to Navigate the Increasingly Symbiotic Dynamic Between Executives and Universities
 Book Review of Closing the Analytics Talent Gap: An...
Guilty or Not Guilty: Weight of Evidence
 You have been invited to serve as a juror...
How Machine Learning Works for Social Good
  Originally published in KDnuggets, Nov 2020. This article...
Diversity and Collaborative Problem Solving to Address Wicked Data Ethics Problems
 The complexity of the ethical issues facing professionals who...

Welcome to The Machine Learning Times (previously Predictive Analytics Times)

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 Originally published in News18.com, Fe 20, 2021 Did YouTube block a chess channel over...

 Originally published in Springboard Blog, Jan 22, 2021. Data science might just be the most...

 Originally published in infoproc.blogspot.com, Feb 7, 2021. This paper shows that models which result...

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     Book Review of Closing the Analytics Talent Gap: An Executive’s Guide to Working with Universitiesby Dr. Jennifer Priestley and Dr. Robert McGrath (CRC Press 2021, part of the Data Analytics Applications series, edited by Jay Liebowitz). We started Enolytics a few years ago in order to fill the gap we saw between the abundance of […]

  • 1 month ago
    Guilty or Not Guilty: Weight of Evidence

     

     You have been invited to serve as a juror in a criminal related case. After hearing testimony, the presiding judge offers a summary of the proceeding. “Evaluate the evidence,” he declares. Whether it was an eyewitness account, an affidavit, an image, or a recording, “it is your responsibility” to assess what was heard. Although “I […]

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      Originally published in KDnuggets, Nov 2020. This article is based on a transcript from Eric Siegel’s Machine Learning for Everyone (on Coursera). View the video version of this specific article Just as businesses tap the value of machine learning, so too can charitable and non-profit organizations. There are a wide variety of ways people […]

  • 3 months ago
    Diversity and Collaborative Problem Solving to Address Wicked Data Ethics Problems

     

     The complexity of the ethical issues facing professionals who work in machine learning, data science, analytics, and related professions have all the hallmarks of a “wicked problem”.  Rittel and Weber, the researchers responsible for coining the term “wicked problems”, believed a more inclusive approach to problem-solving was especially important in diverse and pluralistic societies where […]

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      Straight from the horse’s mouth – the founding chair of the all-new Predictive Analytics World for Climate, Eugene Kirpichov, along with his colleague, Cassandra Xia – read this article for the central role machine learning has to play for climate tech and access the viral “Goodbye, Google” posts that marked their departure from big […]

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      Originally published in KDNuggets. This article is based on a transcript from Eric Siegel’s Machine Learning for Everyone. View the video version of this specific article Nowhere could the application of machine learning prove more important — nor more risky — than in law enforcement and national security. In this article, I’ll review this […]

  • 3 months ago
    Measuring Invisible Treatment Effects with Uplift Analysis

     

      Models make predictions by identifying consistent correlations in what has been observed, but we usually require more than predictions to know what action we should take. For example, knowing that older people are more likely to have heart disease is a good first step, but knowing behaviors or treatments that will reduce the risk […]

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