This tutorial walks you through the required steps to train and get predictions
from your tabular data model in the Google Cloud console.
If you plan to use the Vertex AI SDK for Python, make sure that the service account
initializing the client has the
Vertex AI Service Agent
(roles/aiplatform.serviceAgent
) IAM role.
For this part of the tutorial, you set up your Google Cloud project to use Vertex AI and a Cloud Storage bucket that contains the documents for training your AutoML model.
Set up your project and environment
-
In the Google Cloud console, go to the project selector page.
-
Select or create a Google Cloud project.
-
Make sure that billing is enabled for your Google Cloud project.
- Open Cloud Shell. Cloud Shell is an interactive shell environment for Google Cloud that lets you manage your projects and resources from your web browser. Go to Cloud Shell
- In the Cloud Shell, set the current project to your Google Cloud
project ID and store it in the
projectid
shell variable:gcloud config set project PROJECT_ID && projectid=PROJECT_ID && echo $projectid
Replace PROJECT_ID with your project ID. You can locate your project ID in the Google Cloud console. For more information, see Find your project ID. -
Enable the IAM, Compute Engine, Notebooks, Cloud Storage, and Vertex AI APIs:
gcloud services enable iam.googleapis.com
compute.googleapis.com notebooks.googleapis.com storage.googleapis.com aiplatform.googleapis.com -
Grant roles to your user account. Run the following command once for each of the following IAM roles:
roles/aiplatform.user, roles/storage.admin
gcloud projects add-iam-policy-binding PROJECT_ID --member="USER_IDENTIFIER" --role=ROLE
- Replace
PROJECT_ID
with your project ID. -
Replace
USER_IDENTIFIER
with the identifier for your user account. For example,user:myemail@example.com
. - Replace
ROLE
with each individual role.
- Replace
The Vertex AI User (roles/aiplatform.user
) IAM
role provides access to use all resources in Vertex AI. The Storage Admin
(roles/storage.admin
) role lets you store the document's
training dataset in Cloud Storage.
What's next
Follow the next page of this tutorial to create a tabular dataset and train a classification model.