= Neural backpropagation
{wiki=Neural_backpropagation}
Neural backpropagation, commonly referred to as backpropagation, is an algorithm used for training artificial neural networks. It utilizes a method called gradient descent to optimize the weights of the network in order to minimize the error in predictions made by the model. \#\#\# Key Components of Backpropagation: 1. **Forward Pass**: - The input data is fed into the neural network, and activations are computed layer by layer until the output layer is reached.
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