Stochastic gradient descent (SGD): Revision history

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18 March 2023

  • curprev 13:2913:29, 18 March 2023‎ Walle talk contribs‎ 3,672 bytes +3,672‎ Created page with "{{see also|Machine learning terms}} ==Introduction== '''Stochastic gradient descent''' ('''SGD''') is an optimization algorithm commonly used in machine learning and deep learning to minimize a given objective function. It is a variant of the gradient descent algorithm that performs updates on a randomly selected subset of the data, rather than the entire dataset, at each iteration. This approach offers several advantages, including faster convergence and the abi..."
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