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,...

Machine Learning

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, biased, inequitable, exploitative, or opaque. In this article, I cover six ways that machine learning threatens social justice

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...

A VR Film/Game with AI Characters Can Be Different Every Time You Watch or Play

 Originally posted in MIT Techonology Review, Oct 2, 2020. Agence is neither a movie nor a game, which has frustrated some critics, but it gives a taste of what the future of AI filmmaking could be. The...

AI Can Help Patients—but Only If Doctors Understand It

 Originally published in Wired.com, October 2, 2020. Algorithms can help diagnose a growing range of health problems, but humans need to be trained to listen. Nurse Dina Sarro didn’t know much about artificial intelligence when Duke University...

The Computational Limits of Deep Learning Are Closer Than You Think

 Originally posted to DiscoverMagazine, July 24, 2020. Deep learning eats so much power that even small advances will be unfeasible give the massive environmental damage they will wreak, say computer scientists. Deep in the bowels of the...

Inside TikTok’s Killer Algorithm

 TikTok Wednesday revealed some of the elusive workings of the prized algorithm that keeps hundreds of millions of users worldwide hooked on the viral video app. Why it matters: The code TikTok uses to pick your next...

Traffic Prediction With Advanced Graph Neural Networks

  By partnering with Google, DeepMind is able to bring the benefits of AI to billions of people all over the world.  From reuniting a speech-impaired user with his original voice, to helping users discover personalised apps,...

Multi-Armed Bandits and the Stitch Fix Experimentation Platform

 Multi-armed bandits have become a popular alternative to traditional A/B testing for online experimentation at Stitch Fix. We’ve recently decided to extend our experimentation platform to include multi-armed bandits as a first-class feature. This post gives an...

Looking Inside The Blackbox — How To Trick A Neural Network

 Neural networks get a bad reputation for being black boxes. And while it certainly takes creativity to understand their decision making, they are really not as opaque as people would have you believe. In this tutorial, I’ll...

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...

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