From the CS229A home page
"This class' emphasis is on Applied Machine Learning. Concretely, we want to give you the practical skills needed to get learning algorithms to work. Compared to CS229 (Machine Learning), we cover fewer learning algorithms, and also spend less time on the math and theory of machine learning, but spend much more time on the pratical, hands-on skills (and "dirty tricks") for getting this stuff to work well on an application. More of the homeworks will also focus on giving you practice implementing, modifying and debugging learning algorithms, and less on the mathematical underpinnings of machine learning"
the core idea seems to be that this is a simplified and less rigorous version of CS 229. I am not sure of the tradeoffs between acquiring the "dirty tricks" vs getting a solid grasp of the underlying math (which would presumably result from taking CS229)
Can anyone at Stanford tell me about how much difference is there in the perceived relative toughness of CS229 vs CS 229A? Do CS students take 229A or is it more people from the industry and other (non CS/Math) branches?
Any opinions greatly appreciated.