We're told it's bad, we're told it's wrong. But deep down, we know it's just a misunderstood math operation.
Backpropagation, the unsung hero of neural networks. Without it, our models would be stuck in an era of shallow thinking.
So, what's the deal with the haters? Are they just jealous of our ability to update weights and biases with ease?
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