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Gradient descent is a sort of regional lookup that optimizes a set of numerical parameters by incrementally adjusting them to reduce a loss function. Variants of gradient descent are generally utilized to practice neural networks.[80]A different kind of nearby search is evolutionary computation, which aims to iteratively enhance a list of applicant

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