Self Service ML Pipelines Using Dataprep and AutoML Tables

In this lab you will learn how to use Dataprep in conjunction with AutoML Tables to build and operate your machine learning pipelines.

In this lab, you will learn how to:

• Declare a target schema in Dataprep

• Define data quality rules to declare what "clean data" looks like

• Build a recipe to clean and transform data

• Create parameterized datasets for sources and targets

• Invoke the data pipeline (flow) from plans for training and inference

• Use webhooks to call the AutoML Tables API and execute batch predictions