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minimize our sum squared residual (SSR). To find optimal weights and biases, gradient decent finds a derivative of SSR on each weight and bias in each path, re-calculates each weight and bias, and repeats until it gets the minimum point of SSR or maximum iterations have been reached. The chain rule