Computer_Vision/Chapter01/Feed_forward_propagation.ipynb

Forward Propagation

import numpy as np
def feed_forward(inputs, outputs, weights):       
    pre_hidden = np.dot(inputs,weights[0])+ weights[1]
    hidden = 1/(1+np.exp(-pre_hidden))
    pred_out = np.dot(hidden, weights[2]) + weights[3]
    mean_squared_error = np.mean(np.square(pred_out - outputs))
    return mean_squared_error