Machine Learning Times
Machine Learning Times
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How to Apply Machine Learning to Business Problems
 Originally published in Emerj, April 25, 2020. It’s easy...
Guidebook to the Future of Data Science: How to Navigate the Increasingly Symbiotic Dynamic Between Executives and Universities
 Book Review of Closing the Analytics Talent Gap: An...
Guilty or Not Guilty: Weight of Evidence
 You have been invited to serve as a juror...
How Machine Learning Works for Social Good
  Originally published in KDnuggets, Nov 2020. This article...

data science

How to Apply Machine Learning to Business Problems

 Originally published in Emerj, April 25, 2020. It’s easy to see the massive rise in popularity for venture investment, conferences, and business-related queries for “machine learning” since 2012 – but most technology executives often have trouble identifying where their business might actually apply machine learning (ML) to business problems. With new AI buzzwords being created weekly,

How Can We Fix the Data Science Talent Shortage?

 Originally published in Springboard Blog, Jan 22, 2021. Data science might just be the most buzzed-about job in tech right now, but its pop culture sheen conceals some of the harsh realities of being a fresh graduate in...

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...

What Twitter Learned From The Recsys 2020 Challenge

 Originally published in Towards Data Science on Oct 26, 2020. This year, Twitter sponsored the RecSys 2020 Challenge, providing a large dataset of user engagements. In this post, we describe the challenge and the insights we had...

Split-Second ‘Phantom’ Images Can Fool Tesla’s Autopilot

 Originally posted to Wired.com, Oct 11, 2020. Researchers found they could stop a Tesla by flashing a few frames of a stop sign for less than half a second on an internet-connected billboard. Safety concerns over automated...

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...

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...

On-device Supermarket Product Recognition

 Originally posted on Google AI Blog, Aug 11, 2020. One of the greatest challenges faced by users who are visually impaired is identifying packaged foods, both in a grocery store and also in their kitchen cupboard at...

Looking at Measurement and How We Evaluate the Impact of Reinforcement Learning Over Traditional Predictive Analytics

 Are we really at a new stage of so-called industrial development much like how the car replaced the horse and buggy as the main mode of consumer transportation? This would appear to be the case by some...

A Picture is Worth a Thousand Words: Correspondence Analysis

 Of all the analytic tools that are available to the researcher, perhaps cross tabulations are the most common. A crosstab is nothing more than a table showing the relationship between two or more variables. Where the table only shows...

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