Mastering Python for Finance - Second Edition

Measuring the performance of our model

Using our test data, we can compute the loss and accuracy of our model:

In [ ]:    test_loss, test_acc = model.evaluate(test_scaled_x, test_y)    print('Test loss:', test_loss)    print('Test accuracy:', test_acc)Out[ ]:    6000/6000 [==============================] - 0s 33us/step    Test loss: 0.432878403028    Test accuracy: 0.824166666667

Our model has 82% prediction accuracy.