# Exemplo de um perceptron simples em Python import numpy as np def perceptron(X, y, epochs, learning_rate): weights = np.zeros(X.shape[1]) for _ in range(epochs): for i in range(len(X)): prediction = np.dot(X[i], weights) error = y[i] - prediction weights += learning_rate * error * X[i] return weights # Dados de exemplo X = np.array([[1, 2], [2, 3], [3, 4]]) y = np.array([0, 1, 1]) weights = perceptron(X, y, epochs=10, learning_rate=0.1) print(weights)