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Derivatives: the chain rule behind backpropagation

The derivative: how much the output moves if you nudge the input a little

The derivative answers one question: “If I tweak this weight slightly, does the error go up or down, and by how much?” That is exactly what training needs. Given the derivative, you can step toward lower error — that is gradient descent. Without derivatives, neural networks could not learn at all.

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