Adam is an optimization algorithm used in machine learning and deep learning applications . It's a combination of two other optimization algorithms: RMSprop and Momentum . It was proposed by Diederik P. Kingma and Jimmy Ba

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Adam is an adaptive learning rate algorithm. It customizes the learning rate for each parameter based on its gradient history . This helps the neural network learn efficiently as a whole.  

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Adam adjusts the learning rates for each parameter individually . It calculates an average of the first and second-order moments to scale the learning rates adaptively .