Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Video – Career Paths in Analytics and Data Science and Analytics Team Building
 Event: Machine Learning Week 2021 Keynote: Career Paths in Analytics and...
What Percentage of Your Machine Learning Models Have Been Deployed?
  Do your models usually get deployed? Or are...
Video – Credit Models, Microfinance, and Improving the Lives of Families in the Developing World
 Event: Machine Learning Week 2021 Keynote: Credit Models, Microfinance, and...
Video – Identifying Program Effectiveness for Survivors of Human Trafficking from Muneeb Alam of QuantumBlack
 Event: Machine Learning Week 2021 Keynote: Identifying Program Effectiveness for Survivors...

Original Content

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

How Machine Learning Works for Social Good

  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...

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...

Climate Tech Needs Machine Learning, Says PAW Climate Conference Chair

  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...

Predictive Policing: Six Ethical Predicaments

  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...

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...

Machine Learning: Business Leaders Must Take an Enlightening Look Under Its Hood (New Training Program)

  In this article, I identify unmet learner needs that are addressed by my business-oriented machine learning course series, Machine Learning for Everyone. Machine learning runs the world. It drives millions of business-critical decisions more effectively, guided...

Train Your Team to Avoid This ML Management Pitfall and Unite the Business and Tech Sides

  It’s the age of machine learning. Companies are seizing upon the power of this technology to combat risk, boost sales, cut costs, block fraud, streamline manufacturing, conquer spam, toughen crime fighting, and win elections. But while...

Ethical Machine Learning as a Wicked Problem

 In the 1950 and 1960s, social and behavioral sciences were at the cutting edge of innovation. Scientific techniques and quantitative analyses were being applied to some of the most pressing social problems. The thinking was “If NASA...

Six Ways Machine Learning Threatens Social Justice

 Originally published in Big Think When you harness the power and potential of machine learning, there are also some drastic downsides that you’ve got to manage. Deploying machine learning, you face the risk that it be discriminatory,...

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