adam optimization algorithm

The Adam optimization algorithm is a widely used optimization technique in deep learning that combines the advantages of both AdaGrad and RMSProp algorithms. It dynamically adjusts the learning rate for each parameter based on the first and second moments of the gradients, allowing for faster and more efficient convergence during training.

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