import turicreate as tc # Load the data data = tc.SFrame('cats-dogs.sframe') # Make a train-test split train_data, test_data = data.random_split(0.8) # Create the model model = tc.image_classifier.create(train_data, target='label') # Save predictions to an SArray predictions = model.predict(test_data) # Evaluate the model and save the results into a dictionary metrics = model.evaluate(test_data) print(metrics['accuracy']) # Save the model for later use in Turi Create model.save('mymodel.model') # Export for use in Core ML model.export_coreml('MyCustomImageClassifier.mlmodel')

https://apple.github.io/turicreate/docs/userguide/image_classifier/