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The Perceptron, introduced by Frank Rosenblatt in 1957, is a supervised learning algorithm for binary classification that processes input data through a single-layer neural network. It consists of components such as input layers, weights, biases, and activation functions, and can be trained using various algorithms to minimize prediction errors. While single-layer perceptrons can only handle linearly separable data, multilayer perceptrons can learn more complex patterns, making them essential in the develop

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