import numpy as np """ lets say: Your inputs: x1 =2 (math score), x2 = 3 (science score) Weights: w1 = 0.5, w2 = 0.1 (how important each subject is) Bias: b = 1 """ # activation function def sigmoid(z): return 1 / (1 + np.exp(-z)) # input X = np.array([2, 3]) # wieghts w = np.array([0.5, 0.1]) #bias b = 1 # input(wieghts) product + bias z = np.dot(X, w) + b y = sigmoid(z) print(y)