Nonlinear Optimization
Backpropagation is an algorithm used for training artificial neural networks by calculating the gradient of the loss function with respect to each weight in the network. This method allows for efficient computation of gradients, enabling the network to learn from errors by updating weights in the opposite direction of the gradient, thereby minimizing the loss function. By iteratively applying this process, neural networks can improve their predictions and adjust their parameters based on the feedback received during training.
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