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...

Machine Learning

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 overview of our experimentation platform architecture, explains some of the theory behind multi-armed bandits, and finally shows how

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...

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...

How Machine Learning Works – in 20 Seconds

  This transcript comes from Coursera’s online course series, Machine Learning for Everyone with Eric Siegel. In 57 words, here’s why machine learning’s important: Business needs prediction. Prediction requires machine learning. And machine learning depends on data....

Seven Reasons Budding Data Scientists Need a Machine Learning Course That’s Not Hands-On

  From Coursera’s “Machine learning for Everyone” My new course series on Coursera, Machine Learning for Everyone (free access), is for any learner who wishes to participate in the business deployment of machine learning, no matter whether...

Can GPT-3 Make Analogies?

 Originally published in Medium, Aug 5, 2020. In the early 1980s, Douglas Hofstadter introduced the “Copycat” letter-string domain for analogy-making. Here are some sample analogy problems: If the string abc changes to the string abd, what does...

Dealing with Overconfidence in Neural Networks: Bayesian Approach

 Originally published in Jonathan Ramkissoon Blog, July 29, 2020. I trained a multi-class classifier on images of cats, dogs and wild animals and passed an image of myself, it’s 98% confident I’m a dog. The problem isn’t...

How Not to Know Ourselves

 Originally published in Medium, July 29, 2020. Platform data do not provide a direct window into human behavior. Rather, they are direct records of how we behave under platforms’ influence. Surfing a wave of societal awe and...

Here’s Why Apple Believes It’s An AI Leader—And Why It Says Critics Have It All Wrong

 Originally published in Ars Technica, Aug 6, 2020. Apple AI chief and ex-Googler John Giannandrea dives into the details with Ars. Machine learning (ML) and artificial intelligence (AI) now permeate nearly every feature on the iPhone, but...

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