Backpropagation
Backpropagation is a supervised learning algorithm used for training artificial neural networks. It is a method of updating the weights of the neural network by propagating the error backwards from the output layer to the input layer. The algorithm uses a gradient descent optimization method to minimize the error between the predicted output and the actual output. Backpropagation is a widely used algorithm in deep learning and is used to train various types of neural networks such as feedforward neural networks, convolutional neural networks, and recurrent neural networks.
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