Advance AI: Machine Learning design patterns

In the article, we'll explore some architectural design patterns that support the machine learning model life cycle. The standard data product pipeline, is an iterative process consisting of two phases -- build and deploy -- which mirror the machine learning pipeline.4 During the build phase, data is ingested and wrangled into a form that allows models to be fit and experimented on. During the deploy phase, models are selected and then used to make estimations or predictions that directly engage a user. Users respond to the output of models, creating feedback, which is in turn reingested and used to adapt models.