figure - sample image from the cifar dataset sample flow of how an image is viewed by the cnn is explained in the notebook notebook_cnn_cifar _classifier ipynb it contains rest of the code discussed in this section figure - shows an image from the test dataset it looks like ship and the model correctly identifies the same as well as depicted in this snippet actual image id img_idx actual image label in [ ]y_test[img_idxarray( ]predict label with our model in [ ]test_image =np expand_dims(x_test[img_idx]axis= model predict_classes(test_image,batch_size= / [============================== out[ ]array([ ]dtype=int you can extract and view the activation maps of the image based on what representations are learned and extracted by the conv layers using the get_activationsand display_activationsfunctions in the notebook figure - shows the activations of initial conv layers of the cnn model we just built figure - sample image through cnn layer