Awesome, thanks, I'll definitely test out that dataset! Btw, have you proceeded with any MOOC's after Andrew Ng's ML course? Anyone you'd like to recommend?
Sometimes I'll go read the original paper to learn specific things such as DropConnect for NN (I saw slight improvement on MNIST with DropConnect but not on my other datasets). Same thing for domain knowledge for feature selection, just read relevant papers. Often I have to cross reference certain bits with other papers and reread 10 times before I understand the maths.
It's still my goal to understand convolutional neural nets (and other topics like Bayesian statistics) but I've since stopped on ML and have been learning audio DSP instead. :) Too many things to learn...