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Gradient Descent in Machine Learning

Gradient Descent in Machine Learning

What is Gradient Descent in Machine Learning?

Gradient descent is an optimization algorithm that updates model parameters by stepping opposite the gradient of a loss function, reducing error over iterations (often on mini-batches).

Variants like SGD, Adam, and AdaGrad change step-size and momentum behavior.

Authority: Wikipedia: Gradient descent

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