Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Watch 3 Videos from Coursera’s New “Machine Learning for Everyone”
  I’m pleased to announce that, after a successful...
97 Things About Ethics Everyone In Data Science Should Know
 Every now and then an opportunity comes along that...
Machine Learning is Transforming Modern Healthcare
 The pandemic has propelled the adoption of innovation and...
It’s a Bird, It’s a Plane, It’s a Classified Flying Object
 How Computer Vision Is Used To Classify Objects. Featuring...

Industry News

Applying Occam’s Razor to Deep Learning

 Originally published in Memo’s Island, December 15, 2019 Preamble: Changing concepts in machine learning due to deep learning Occam’s razor or principle of parsimony has been the guiding principle in statistical model selection. In comparing two models, which they provide similar predictions or description of reality, we would vouch for the one which is less

Data Project Checklist

 Originally published in Fast.ai, January 7, 2020. As we discussed in Designing Great Data Products, there’s a lot more to creating useful data projects than just training an accurate model! When I used to do consulting, I’d...

How Our Primary Model Works

 Originally published in FiveThirtyEight, January 9, 2020 Here at FiveThirtyEight, we’ve never built a complete back-to-front model of the presidential primaries before. Instead, in 2008, 2012 and 2016, we issued forecasts of individual primaries and caucuses on...

The 4 Hottest Trends in Data Science for 2020

 Originally published in Towards Data Science, January 8, 2020 2019 was a big year for all of Data Science. Companies all over the world across a wide variety of industries have been going through what people are...

The Problem with Hiring Algorithms

  Originally published in EthicalSystems.org, December 1, 2019 In 2004, when a “webcam” was relatively unheard-of tech, Mark Newman knew that it would be the future of hiring. One of the first things the 20-year old did,...

5 Statistical Traps Data Scientists Should Avoid

 Originally published in KDnuggets, October 2019. Fallacies are what we call the results of faulty reasoning. Statistical fallacies, a form of misuse of statistics, is poor statistical reasoning; you may have started off with sound data, but...

Why Machine Learning at the Edge?

 Originally published in SAP Blogs, October 16, 2019. For today’s leading deep learning methods and technology, attend the conference and training workshops at Deep Learning World Las Vegas, May 31-June 4, 2020.   Machine learning algorithms, especially deep learning...

Machine Learning & SEO: Where Are We Now?

 Originally published in DigitalDoughnut, October 25, 2019 For many in the SEO world, the idea of machine learning influencing the industry is making substantial waves. The technology inevitably promises to alter the way in which business is...

How to Leverage Predictive Analytics for Employee Retention

 Originally published in TechRepublic, November 7, 2019. Competition for skilled tech workers is fierce, so a new program actually predicts when an employee is considering resignation, and how you can implement retention. Crystal balls, fortune cookies and...

How Machine Learning Pushes Us to Define Fairness

 Originally published in Harvard Business Review, November 6, 2019. Bias is machine learning’s original sin. It’s embedded in machine learning’s essence: the system learns from data, and thus is prone to picking up the human biases that...

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