The model-building phase consists of many substeps, as indicated earlier, such as the selection of an appropriate machine learning algorithm, training the model, testing it, evaluating the model to determine whether the objectives have been achieved, and, if not, entering into the retraining phase by either selecting the same algorithm with different datasets or selecting an entirely new algorithm till the objectives are reached.