In the preceding section, we created our model to classify the messages as spam and non-spam. Now, let's convert that into the Core ML model so that we can use that in an IOS app.

To create a core-ML model, append the following lines to the preceding code and run them. This will create a .mlmodel file:

# importing the library
import coremltools

# convert to fitted model in to coreml model
coreml_model = coremltools.converters.sklearn.convert(text_clf, "message", "spam_or_not")

#set parameters of the model
coreml_model.short_description = "Classify whether message is spam or not"
coreml_model.input_description["message"] = "TFIDF of message to be classified"
coreml_model.output_description["spam_or_not"] = "Whether message is spam or not"

#save the model
coreml_model.save("SpamMessageClassifier.mlmodel")

Now, you can take the generated SpamMessageClassifier.mlmodel file and use this in your Xcode.