started separating out the weight and bias terms - it does make the code much cleaner, although there's a little more to keep track of. probably easier to debug and modify. finished changing it up for the neural net core and autoencoder, next up is the softmax classifier, and lastly, the deep autoencoder
using this separated weight and bias format makes things slower - will need to look into this later, but for now, I'll switch back to the combined version
Heavily cleaned up the structure of the code, added a setup.py file which uses distutils (even though setuptools is recommended, this is a fairly simple build, so didn't see the need to use it) to package the code. This can now be installed on a system and imported like any other python package. I'm sure there's still lots of ways to improve all this, but for now, this is a lot cleaner to work with. Next commit will add config files and logging
starting to fix errors in the code
starting to correct the deep autoencoder class
Merge branch 'master' into weights_and_biases
whatever
got the sae demo working again
hopefully finished with this merging crap