What are some of the most common optimization algorithms used to train deep learning models?

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Krishnapriya Rajeev · Answer

Some of the most common and sophisticated optimization algorithms used to train deep learning models are: Stochastic Gradient Descent (SGD): This is the most commonly used optimization algorithm in deep learning. It updates the model's parameters in the direction of the steepest gradient of the loss function.AdaGrad: This algorithm adapts the learning rate for each parameter based on the historical gradient information, giving smaller learning rates to parameters associated with frequently occurring features.RMSProp: This algorithm divides the learning rate by a running average of the magnitudes of recent gradients for each parameter, thereby making it less sensitive to noisy gradients.Adam: This algorithm combines the ideas of momentum and AdaGrad, resulting in an adaptive learning rate that changes according to the momentums of gradients and a running estimate of the second moment of the gradients.

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What are some of the most common optimization algorithms used to train deep learning models?

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