We finished the first part of the Stanford ml-class course. Other than the backpropagation programming exercise, the rest have been easy enough for the people with the right programming/algebra skills.
The most interesting part comes next. I never studied SVM in my university years so it will be a new area for me. I expect this will help me to understand how easy is the course for people without previous machine learning skills. I’ll keep you updated.
Also the big news is Stanford has anounced new courses for 2012:
- CS 101 by Nick Parlante @ cs101-class.org
- Natural Language Processing by Dan Jurafsky and Chris Manning @ nlp-class.org
- Software Engineering for SAAS by Armando Fox and David Patterson @ saas-class.org
- Human-Computer Interfaces by Scott Klemmer @ hci-class.org
- Game Theory by Matthew Jackson and Yoav Shoham @ game-theory-class.org
- Probabilistic Graphical Models by Daphne Koller @ pgm-class.org
- Machine Learning by Andrew Ng @ jan2012.ml-class.org (Same class as current ml-class.org)
- Cryptography by Dan Boneh @ crypto-class.org
- Lean Launchpad by Steve Blank @ launchpad-class.org
- Technology Entrepreneurship by Chuck Eesley @ venture-class.org
I really like the diversity of the courses (from soft skills like enterpreneurship to math like game theory, including a course about human computer interfaces).
I would like to sign up for the Software Engineering course, but I’ll need to find some extra time for it.