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Optimization in Machine Learning: Gradient-Based and Non-Gradient-Based Methods
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Which of the following is a gradient-based optimization method?
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A
Stochastic Gradient Descent (SGD)
💡 Explanation:
Stochastic Gradient Descent (SGD) is an iterative optimization algorithm that uses the gradient of the loss function to update the model parameters. It is a widely used method in machine learning for training neural networks and other models.