Statistical Machine Learning Circa 1989

I've always been a massive fan of statisticians whose work is rigorous yet practical, with emphasis on modeling. People like Box, Cox, Hastie, and Tibshirani obviously come to mind.  So too, of course, do Leo Brieman and Jerry Friedman.  

I had the good luck to stumble into a week-long intensive lecture series with Jerry Friedman in 1989, a sort of summer school for twenty-something assistant professors and the like.  At the time I was a young economist in DC at the Federal Reserve Board, and the lectures were just down the street at GW.

I thought I would attend to learn some non-parametrics, and I definitely did learn some non-parametrics.  But far more than that, Jerry opened my eyes to what would be unfolding for the next half-century -- flexible, algorithmic, high-dimensional methods -- the statistics of "Big Data" and "machine learning".  

I just found the binder containing his lecture notes.  The contents appear below.  Read the opening overview, "Modern Statistics and the Computer Revolution".  Amazingly prescient.  Remember, this was 1989!

[Side note:  There I also had the pleasure of first meeting Bob Stine, who has now been my esteemed Penn Statistics colleague for more than 25 years.]