The key thing to be tested in the project is the mobile machine learning model. So, independent of the mobile application, the model needs to be tested thoroughly. 

We have already seen what things should be focused on while testing the machine learning model. The training data, test data, and cross-validation need to be considered while testing the model. The performance measure of the chosen model to be measured. For each run of the clear record keeping of the results to be done, so that we clearly know for a delta change in feature set of the input data, what is the delta change in output. All the concepts explained in Chapter 1, Introduction to Machine Learning on Mobile, related to accuracy, precision, recall, error, and so on should be understood clearly by an engineer testing machine learning models. Also, for each type of algorithm, the error and performance measure metrics vary, which should be taken into due consideration while testing the models. Testing machine learning models is itself worth a book and dwelling on the details in this book is out of scope.