Couple o' notes

[tigershen23]

Hey Jason, just dropping a couple of thoughts here for ya:

• Not sure how much time you want to spend on 1-machine-learning, but there's always Andrew Ng's canonical Coursera course; https://docs.google.com/document/d/1AISQIb2LVlMzN2tmTbMg3zsoBg9n4xk7HO12hEYgoIw/edit is the best collection of notes I've seen on it, if you want to skim
• Again unsure of your intended scope, but for 2-neural-nets I might generalize and add a few fundamentals to the mix: backprop, SGD, optimizers, activation functions, loss functions, techniques to combat overfitting. I think a solid basis in each of these things (which I hope to one day have) would go a long way towards making current research easier to grok.
• 5-rnns-cnns looks scary and intense; since I don't understand a lot of the verbiage here, I just wanted to clarify if your intent is to study the intersection and combination between RNNs and CNNs specifically, or to survey more advanced NN techniques in general.

Cheers!