what is mlp in machine learning

A Multilayer Perceptron (MLP) is a type of feedforward artificial neural network that consists of fully connected neurons with a nonlinear activation function. It is a fully connected multi-layer neural network with at least three layers: an input layer, an output layer, and at least one hidden layer. If it has only one hidden layer, it is called a shallow MLP, and if it has more than one hidden layer, it is called a deep MLP. The MLP learning procedure involves propagating data forward from the input layer to the output layer, calculating the error based on the output, and backpropagating the error to adjust the weights in the network with the goal of minimizing the cost function. MLPs can be used for a variety of tasks, including sentiment analysis.