I am quite new in the AI field. I am trying to create a neural network, in a language (Dart) where I couldn't find examples or premade libraries or tutorials. I've tried looking online for a strictly "vanilla" python implementation (without third-party libraries), but I couldn't find any.
I've found a single layer implementation, but it's done only with matrices and it's quite cryptic for a beginner.
I've understood the idea between the feed forwarding, a neuron calculates the sum of its inputs, adds a bias and activates it.
But I couldn't find anything a neuron-level explanation of the math behind backpropagation. (By neuron-level I think of the math down to the single neuron as a sequence of operations instead of multiple neurons treated as matrices).
What is the math behind it? Are there any resources to learn it that are suitable as a beginner?