Hacker's Guide to Neural Networks
Thanks for the upvotes! I'm a little conflicted about this being linked around too much because it is still very much work in progress. I work on this guide on a side because I think there's a lot of interest in these models out there, and not enough explanations.<p>On a related note, some of you might also be interested in a Stanford CS class I'll be co-teaching with my adviser next quarter. It will be focused primarily on Convolutional Networks (but a lot of the learning machinery is generic):<p>CS231n: Convolutional Neural Networks for Visual Recognition
<a href="http://vision.stanford.edu/teaching/cs231n/" rel="nofollow">http://vision.stanford.edu/teaching/cs231n/</a><p>I hope to make a lot of the materials/code freely available so everyone can follow along, and I will continue my work on this guide in parallel whenever I can squeeze in time. (And I'd be happy to hear any feedback on the content/style/presentation)