Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
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...
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...

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 Originally published in Chip Huyen, Dec 27, 2020. After talking to machine learning and...

 Originally published in GitHub.com. A curated list of the latest breakthroughs in AI by...

 Originally published in The Netflix Tech Blog, Dec 10, 2020. Netflix is pioneering content...

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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 […]

  • 2 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 […]

  • 2 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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      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 by concrete evidence in the form of data – determining whom to call, mail, approve, test, diagnose, warn, […]

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      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 there are so many how-to training programs for hands-on techies, there are practically none that also serve business […]

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