
CS 281B: Statistical Learning Theory (2014) - kercker
http://people.eecs.berkeley.edu/~jordan/courses/281B-spring04/
======
rm999
To put it in perspective Michael Jordan is one of the pioneers of the modern
approach to statical machine learning. It's very cool to see his course notes
from 12 years ago when many schools didn't even offer basic machine learning
courses.

Learning theory is a math-heavy (proof-heavy) subfield of machine learning
that studies what's possible and why some of the methods work as well as they
do. Unless you have a strong math background and are already fairly well-
versed in machine learning, I'd first take practical classes. Learning theory
is the last class I took in grad school and I really enjoyed it.

------
cuchoi
For those who prefer videos, here is the MIT version of the course:

9.520 - Statistical Learning Theory and Applications, Fall 2015
[https://www.youtube.com/watch?v=6AWZS4Ho2Z8&list=PLyGKBDfnk-...](https://www.youtube.com/watch?v=6AWZS4Ho2Z8&list=PLyGKBDfnk-
iDj3FBd0Avr_dLbrU8VG73O)

~~~
rdudekul
Here's one from CMU (Spring 2016): Statistical Machine Learning

[https://www.youtube.com/watch?v=zcMnu-3wkWo&list=PLTB9VQq8Wi...](https://www.youtube.com/watch?v=zcMnu-3wkWo&list=PLTB9VQq8WiaCBK2XrtYn5t9uuPdsNm7YE)

------
MarkG509
Earlier this year, I retired (voluntarily) from a large company after 32
years. Now that I have time to breath/think/sleep, I actually 'audit' many of
the on-line courses I find mentioned here. Great fun. Thanks!

~~~
curiousgal
That's really cool! I am still in my early twenties and I find that rather
inspiring. Thank you!

------
njohnson41
This should be marked (2004), not (2014).

------
selmat
Here is it from 2014:
[http://people.eecs.berkeley.edu/~jordan/courses/281A-spring1...](http://people.eecs.berkeley.edu/~jordan/courses/281A-spring14/)

...unfortunately 2014 version has fewer study materials

~~~
randcraw
Access to all the readings at this link has been blocked. Only the newer
syllabus is visible.

------
georgeek
The reason why the class from 2014 doesn't have a lot of the material is
because a big part of it is based on Prof Jordan's future book on Statistical
Learning Theory. Another great study of his:
[http://www.nowpublishers.com/article/Details/MAL-001](http://www.nowpublishers.com/article/Details/MAL-001)

------
astrosi
Looks like the homeworks for this are not available.

------
tomrod
It would be interesting to see if there is anything similar for text mining.

------
zump
How can I get VC's to fund my dimension?

~~~
arcanus
Along those lines, I've heard less press about statistical learning start ups
than some of the recent deep learning work.

Anyone know of some recent ventures in this space? Anyone to keep an eye on?

~~~
zump
Because a kernel SVM is a neural net with one hidden layer?!

