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You have more chances of learning if you understand the math behind. But if you still are after some code here is mine: http://htmlpreview.github.io/?https://g
by xchip 9y ago
You have more chances of learning if you understand the math behind.
But if you still are after some code here is mine: http://htmlpreview.github.io/?https://github.com/aguaviva/ArtificialIntelligence/blob/master/GenericDistRegression.html http://htmlpreview.github.io/?https://github.com/aguaviva/Ar...
- tropin 9y agoIt would be great to add some context to the demo.
- scarlac 9y agoI agree. A solid understanding of why it works is still a requirement if you want to do something productive with neural networks. But as someone who has been taking video courses and seen youtube videos, somehow this was the final step I needed to get started on my idea. It was easy to follow along, the code was nice and clean (most importantly without convoluted variable naming), and the immediately-interactive code made it quick to test a few things, rather than having to fork a project, NPM install a thousand dependencies and then actually do some coding.
- criveros 9y agoWhere does one go to learn the math behind it?
- tnecniv 9y agoThat depends if you know calculus, preferably multivariable.
- b45 9y agoHere is a simple start! https://www.youtube.com/watch?v=N4gDikiec8E https://www.youtube.com/watch?v=N4gDikiec8E
- soVeryTired 9y agoModule one of Andre Karpathy's course is the most intuitive explanation I've seen. Working through backprop equations was a major hassle until I read those notes. http://cs231n.github.io/ http://cs231n.github.io/