Statistical Prediction
Backpropagation is an algorithm used to train artificial neural networks by calculating the gradient of the loss function with respect to each weight by the chain rule, allowing the model to update its weights in order to minimize errors. This process involves a forward pass where the input data is processed and a backward pass where gradients are computed and weights are adjusted. It's a critical component in effectively training deep learning models and achieving high accuracy.
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