multilayer perceptron
A multilayer perceptron is a type of artificial neural network that consists of multiple layers of interconnected perceptrons or artificial neurons. It is a feedforward neural network, where information flows from the input layer through one or more hidden layers to the output layer. The perceptrons in each layer calculate weighted sums of their inputs and then apply a non-linear activation function. The weights in the network are adjusted through a process called backpropagation, which involves iteratively updating the weights based on the difference between the predicted and actual outputs. This allows the multilayer perceptron to learn and make predictions on complex datasets, offering enhanced capabilities in solving various machine learning tasks, such as classification, regression, and pattern recognition.
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