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Which courses did you take out of interest?

I struggle with the mathematics used in neural networks. I can understand code but as soon as I start to see calculus my brain freezes over. Does anyone know of a good online course that can give me a crash course in the mathematics required for neural networks?

My CS bachelors covered this, but I was lazy and drank too much beer. Now 20 years later I want to understand it properly.

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I've taken Andrew Ng's Machine Learning class, Daphne Koller's Probabilistic Graphical Models class, Dan Jurafsky and Christopher Manning's Natural Language Processing class, and currently Geoff Hinton's Neural Networks class.

I have spent a lot of time on Khan Academy to learn the calculus. In my experience you can get by with a surprisingly small amount of calculus, but it happens to be a small amount from a high level.

For example, backpropagation is just repeated application of the chain rule. Did take a while to get a handle on the derivatives, but it's worth it.

Do the theano deep learning tutorials. And keep hacking away at the math--you need it, but it eventually sinks in and becomes reasonably intuitive. Starting with code helped me grasp the math (I'm also much more comfortable reading code than math).

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