Learn Python Fast: 2 Books in 1: Python Machine Learning and Data Science. The complete starter guide for total beginners + practical exercises by Computer Programming Academy

Author:Computer Programming Academy [Academy, Computer Programming]
Language: eng
Format: azw3
Published: 2020-05-18T16:00:00+00:00

plt.ylim([0, 1] )

predicted_label = np.argmax(predictions_array )

thisplot[predicted_label].set_color('red' )

thisplot[true_label].set_color('blue')”

Now, for example, you may want to generate a prediction for a specific picture in the testing data set. You can do this by utilizing the command below:

“Grab an image from the test datase t

img = test_images[0 ]

print(img.shape)”

“(28, 28)”

To use the “tf.keras” models to generate this prediction, the picture must be added to a list, since these models have been optimized to generate predictions on a “collection of dataset” at a time. Use command below to accomplish this:

“# Add the image to a batch where it's the only member .

img = (np.expand_dims(img,0) )

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