3 ms·
Gee, guys, looking at the list of topics, a huge fraction, likely over 50%, of the material goes back to programs in operations research, statistics, and the m
by graycat 13y ago
Gee, guys, looking at the list of
topics, a huge fraction, likely over
50%, of the material goes back to
programs in operations research,
statistics, and the mathematical
sciences from about 1970 on.
Nearly the only thing new is the
collection of sample applications.
From what I've seen, the quality
of the content of the current ML
courses is way below that going
back to 1970.
Warning: History shows that the
US economy looked at the material
in operations research, statistics,
and the mathematical sciences and
rolled their eyes, did a big upchuck,
laughed, turned, and walked away.
One might look for alarms from their
hype and fad detectors.
- rahimiali 13y agoa good machine learning course might indeed cover 1940-1980s operations research (nonlinear optimization, linear/quadratic programming, dynamic programming), and statistics from 1970-1990s (graphical models, markov chain monte carlo methods, measures of model capacity). i'd say the field borrows the most useful bits from these fields and finds good honest use in many real life problems today. and i agree that there's a lot of unwarranted hype that leads to a lot of well-deserved skepticism.