Vertex AI Model Builder SDK: Training and Making Predictions on an AutoML Model
LINK : QWIKLABS 3 JAM
Overview
In this lab, you learn to use Vertex AI Python client library to train and make predictions on an AutoML model based on a tabular dataset. Alternatively, you can train and make predictions on models by using the gcloud command-line tool or by using the online Cloud Console.
Learning objectives
Create a Vertex AI model training job.
Train an AutoML tabular model.
Deploy the model resource to a serving endpoint resource.
Make a prediction by sending data.
Undeploy the model resource.
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.