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What is Stochastic Gradient Descent Overview about?

Stochastic search methods, also known as stochastic optimization methods, utilize randomness to solve complex optimization problems and are effective in various fields like machine learning and engineering. These methods often employ heuristic search techniques and include algorithms inspired by biological processes, such as Genetic Algorithms and Simulated Annealing. Stochastic Gradient Descent (SGD) is a specific example that improves computational efficiency by using a single randomly selected sample for

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