
To conclude what we have covered so far, it's clear that when building a model, the trainer selection is not the most difficult part. AutoML is able to suggest a list with the best models, due to the evaluation metrics which accompany every model. What is much more complex (and time-consuming) is the data preparation which, along with the training pipeline, builds a model ready to make predictions.