Self Service ML Pipelines Using Dataprep and AutoML Tables

In this Project, you will:

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.

1.5 hours
Intermediate
No download needed
Shareable certificate
English
Desktop only

This is a self-paced lab that takes place in the Google Cloud console. In this lab you will learn how to use Dataprep in conjunction with AutoML Tables to build and operate your machine learning pipelines.

Skills you will develop

  • Data Management

  • Google Cloud Platform

  • Dataprep

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