Working on cell 10 in machine learning for classifying cats and dogs. I have been going around in circles trying to get the probabilities into the right form so I can pass them into plot images, but I am now so lost I can’t think straight. At one time I could print the probabilities and they were tuples so I could then use them to predict, but I tweaked some of the numbers in the model, and now I get a bunch of 1.0.
Can someone help me out here? I’m getting frustrated and need a point in the right direction.
Your code so far
probability_model = tf.keras.Sequential([model, tf.keras.layers.Softmax()]) print(type(probability_model)) predictions = probability_model.predict(test_data_gen)#predictions is numpy.ndarray probabilities = #type=array for p in predictions: print(np.round(p)) probabilities.append((p)) print(predictions) print(probabilities) print(test_data_gen) img =  for i in test_data_gen: img.append(i) #plotImages(img)
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Challenge: Cat and Dog Image Classifier
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