<jupyter_start><jupyter_text>So the test accuracy comes out to be 81% and train accuracy comes out to be 86%<jupyter_code>import numpy as np
from keras.preprocessing import image
test_image = image.load_img("D:\img_1.jpg", target_size = (64, 64))
test_image = image.img_to_array(test_image)
test_image = np.expand_dims(test_image, axis = 0)
result = classifier.predict(test_image)
train_data.class_indices
if result[0][0] == 1:
    prediction = 'dog'
else:
    prediction = 'cat'
    
prediction
import numpy as np
from keras.preprocessing import image
test_image = image.load_img("D:\img_2.jpg", target_size = (64, 64))
test_image = image.img_to_array(test_image)
test_image = np.expand_dims(test_image, axis = 0)
result = classifier.predict(test_image)
train_data.class_indices
if result[0][0] == 1:
    prediction = 'dog'
else:
    prediction = 'cat'
    
prediction<jupyter_output><empty_output>
StarcoderdataJupyterStructuredCleanDedup