So all the hype these days is around “AI”, as opposed to “machine learning” (though I’ve yet to hear an exact distinction between the two), and one of the tools that seems to get talked about most is Google’s Tensorflow.
I wanted to get playing around with Tensorflow and RNN’s a little bit, since they’re not the type of machine learning I’m most familiar with, with a low investment in time to see what kind of outputs I could come up with.
A little digging and I came across this tutorial, which is a pretty good brief overview intro to RNNs, and uses Keras and computes things character-wise.
This is turn lead me to word-rnn-tensorflow, which expanding on the works of others, uses a word-based model (instead of character based).
I wasn’t about to spend my whole weekend rebuilding RNNs from scratch – no sense reinventing the wheel – so just thought it’d be interesting to play around a little with this one, and perhaps give it a more interesting dataset. Shakespeare is ok, but why not something a little more culturally relevant… like I dunno, say the scripts from a certain cartoon featuring a dysfunctional foul-mouthed spy agency?