Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Climate Tech Needs Machine Learning, Says PAW Climate Conference Chair
  Straight from the horse’s mouth – the founding...
Predictive Policing: Six Ethical Predicaments
  Originally published in KDNuggets. This article is based...
Measuring Invisible Treatment Effects with Uplift Analysis
  Models make predictions by identifying consistent correlations in...
Machine Learning: Business Leaders Must Take an Enlightening Look Under Its Hood (New Training Program)
  In this article, I identify unmet learner needs...

Original Content

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 to play for climate tech and access the viral “Goodbye, Google” posts that marked their departure from big

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,...

Transitions: Predicting The Next Event

 Models predicting the potential spread of the COVID-19 pandemic have become a fixture of American life. Many of these models use typical demographic data, coupled with underlying medical conditions, infection rates, etc. Indeed, the spread of this...

Coursera’s “Machine Learning for Everyone” Fulfills Unmet Training Requirements

  My new course series on Coursera, Machine Learning for Everyone (free access), fulfills two different kinds of unmet learner needs. It’s a conceptually-complete, end-to-end course series – its three courses amount to the equivalent of a...

Segmentation and RFM Analysis in the World of Wine and Spirits

 Segmentation is a hot word these days, and it should be. No matter your business, one direct way to increase revenue is better communication with sales prospects. And better communication is a direct result of the granularity...

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