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For what it's worth, I didn't read the article at all, went straight to the final code, and had no issue reading or understanding it. The variable names seem fi
by nilkn 8y ago
For what it's worth, I didn't read the article at all, went straight to the final code, and had no issue reading or understanding it. The variable names seem fine to me. They're actually quite good, and I liked the convention for naming partial derivatives.
This code is designed to be read by someone who is pretty familiar with the underlying concepts. If you don't really know how a neural network works or how gradient descent is applied to update the weights, that's your blocker, not the variable names I saw here.
- deytempo 8y agoWell then they should get rid of the misleading title “from scratch” it makes it sound like they are going to explain it without beltching out a bunch of abstract math. I’m really annoyed that everyone pretends that you need math to explain a NN. I have done plenty of them without numpy or math using just arrays and loops.
- nilkn 8y agoThis is not abstract math, and the article does explain what it's doing before presenting the code snippets. How can you explain or implement gradient descent without math? At some point I think you have to accept that this is a topic that involves math, and you're way better off understanding it on those terms rather than trying to avoid it.