Creating an AutoML training pipeline

Sometimes, it's necessary to retrain a model that you trained in AutoML. ML models can degrade over time if the relationship between your data and your target variable changes. This is true for all ML models, not just ones generated by AutoML.

Imagine, for example, that you build an ML model to predict demand for frozen pizza at a supermarket, and then one day, a famous pizza chain sets up shop next door. It's very likely that consumer buying behavior will change, and you will need to retrain the model. This is true for all ML models.

Luckily, AMLS has specialized ML pipeline steps built specifically for retraining models. In this section, we are going to use one of those steps, the AutoML step. The AutoML step lets you retrain models easily whenever you want, either with a push of a button or on a schedule.

Here, you will build a two-step ML pipeline where you will first train a model with an AutoML step and register it with...