Retrospective on “On Moving From Statistics to Machine Learning”

My old piece is getting traction thanks to a share on Hacker News, where some of the most insufferable tech guys in California try to dissect in the comments whether I have deep-seated psychological issues. Also, I was mentioned in this blog post at Win Vector LLC, which offers a fair and very good critique … Continue reading Retrospective on “On Moving From Statistics to Machine Learning”

Why Do So Many Practicing Data Scientists Not Understand Logistic Regression?

The U.S. Weather Service has always phrased rain forecasts as probabilities. I do not want a classification of “it will rain today.” There is a slight loss/disutility of carrying an umbrella, and I want to be the one to make the tradeoff. Dr. Frank Harrell, https://www.fharrell.com/post/classification/ This is coming from personal experience and from multiple … Continue reading Why Do So Many Practicing Data Scientists Not Understand Logistic Regression?

What Makes an Interview Homework Assignment Good or Bad?

Someone reached out to me recently to critique their homework interview problems. I thought it would be useful for them if I wrote up a general overview of how I think about the hiring process and how homework problems fit in to the whole process. I should also note that absolutely nothing here is directly … Continue reading What Makes an Interview Homework Assignment Good or Bad?

AI Will Not Reduce Discrimination in Hiring Practices. Does the Public Agree?

This is the 1st article in a 2-part series on the use of AI in hiring. The 2nd part will be available on Wednesday, January 8th. Arvind Narayanan somewhat recently put out a presentation called “How to recognize AI snake oil.” It’s incredible, and I highly recommend reading it in full. He also has a … Continue reading AI Will Not Reduce Discrimination in Hiring Practices. Does the Public Agree?