Statistical Learning Part III by Steve Miller.
From the post:
I finally got around to cleaning up my home office the other day. The biggest challenge was putting away all the loose books in such a way that I can quickly retrieve them when needed.
In the clutter I found two copies of “The Elements of Statistical Learning” by Trevor Hastie, Robert Tibshirani and Jerome Friedman – one I purchased two years ago and the other I received at a recent Statistical Learning and Data Mining (SLDM III) seminar taught by first two authors. ESL is quite popular in the predictive modeling world, often referred to by aficionados as “the book”, “the SL book” or the “big yellow book” in reverence to its status as the SL bible.
Hastie, Tibshirani and Friedman are Professors of Statistics at Stanford University, the top-rated stats department in the country. For over 20 years, the three have been leaders in the field of statistical learning and prediction that sits between traditional statistical modeling and data mining algorithms from computer science. I was introduced to their work when I took the SLDM course three years ago.
Interesting discussion of statistical learning with Q/A session at the end.