Stochastic Gradient Descent (SGD) is an iterative algorithms used for objective function optimization used in machine learning models.
Stochastic Gradient Descent (SGD) is an iterative algorithms used for objective function optimization used in machine learning models. It is often considered a stochastic approximation approach to the Gradient Descent algorithm that is commonly used in machine learning optimization problems.
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