You'll notice at the bottom for the training time. That's immense.
The reason I'm encouraging horse power for practical use is to reduce training time to something meaningful for iteration use via distributed means.
I have visualization techniques built in to the lib to help come up with an optimal model so you know it works well, I still need to implement grid search and some other stuff.
My timeline is within the next month or so to have all of this done. I will have the stanford recursive neural tensor nets and the conv nets done here shortly. The next part will be distributed GPUs ;).
I hope to make this as practical as possible for people. The next obvious step after training time is practical and easy to do is wrappers for common tasks.
