Create and Run ML Pipelines with Vertex Pipelines
LINK : QWICKLABS 3 JAM 30 MENIT
LINK : QWICKLABS 3 JAM 30 MENIT
LINK : QWICKLABS 3 JAM 30 MENIT
LINK : QWICKLABS 3 JAM 30 MENIT
Overview
In this lab, you will learn how to create and run ML pipelines with Vertex Pipelines.
Learning objectives
Use the Kubeflow Pipelines SDK to build scalable ML pipelines.
Create and run a 3-step intro pipeline that takes text input.
Create and run a pipeline that trains, evaluates, and deploys an AutoML classification model.
Use pre-built components, provided through the google_cloud_pipeline_components library, to interact with Vertex AI services.
Schedule a pipeline job with Cloud Scheduler.
Setup
For each lab, you get a new Google Cloud project and set of resources for a fixed time at no cost.
Sign in to Qwiklabs using an incognito window.
Note the lab's access time (for example, 02:00:00), and make sure you can finish within that time. There is no pause feature. You can restart if needed, but you have to start at the beginning.
When ready, click Start lab.
Note your lab credentials (Username and Password). You will use them to sign in to the Google Cloud Console.
Click Open Google Console.
Click Use another account and copy/paste credentials for this lab into the prompts. If you use other credentials, you'll receive errors or incur charges.
Accept the terms and skip the recovery resource page.
Do not click End Lab unless you have finished the lab or want to restart it. This clears your work and removes the project.
Activate Cloud Shell
Cloud Shell is a virtual machine that contains development tools. It offers a persistent 5-GB home directory and runs on Google Cloud. Cloud Shell provides command-line access to your Google Cloud resources. gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab completion.