Is there any way I can implement the same code in Jupyter notebook?

[tharunnayak14]

import numpy as np
from google.colab import files
from keras.preprocessing import image

uploaded = files.upload()

for fn in uploaded.keys():

# predicting images
path = '/content/' + fn
img = image.load_img(path, target_size=(300, 300))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)

images = np.vstack([x])
classes = model.predict(images, batch_size=10)
print(classes[0])
if classes[0] > 0.5:
    print(fn + " is a human")
else:
    print(fn + " is a horse")

[maurizioscibilia]

Hi @tharunnayak14,
in every week material you can find the Colab version and the Lab that gets executed on the Coursera Platform. Just look for it.