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 calling a digital transformation. That is, businesses are taking traditional business processes such as hiring, marketing, pricing, and
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,...
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...
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...
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...
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...
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...
