Deep Learning, Machine Learning, Artificial Intelligence, Loss Function, Neural Networks.
is an example of how to calculate it: # define true labels and predicted probabilities y_true = np.array([0, 1, 1, 0]) y_pred = np.array([0.1, 0.9, 0.8, 0.3]) # calculate the binary cross-entropy loss loss = -(y_true * np.log(y_pred) + (1 - y_true) * np.log(1 - y_pred)).mean() # print the loss