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What is Common Optimizers in Machine Learning about?

Optimizers are algorithms that minimize the loss function by adjusting weights and biases during training. Common optimizers include Gradient Descent, Stochastic Gradient Descent, Momentum, and Adam, each with unique methods for updating weights. The Adam optimizer specifically combines techniques from RMSProp and Momentum to adapt learning rates for each parameter.

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rahul.2nd.55

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EN