Learning rules in Deep Neural Network #ai #learning #hebbian #perceptron #competitive #gradient

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The learning rule in neural networks is a set of methods and algorithms used to adjust the weights of the network based on the input data and the error of the network's output. The goal of these adjustments is to minimize the error and improve the network's performance over time. #Backpropagation #GradientDescent #LearningRule #neuralnetworks #LearningRule #ai #learning #hebbian #perceptron #memory
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