Use the Google Cloud Console to create a tabular dataset and use it to train a classification model.
This tutorial has several pages:
Creating a tabular dataset and training an AutoML classification model.
Each page assumes that you have already performed the instructions from the previous pages of the tutorial.
Create a tabular dataset
In the Google Cloud Console, in the Vertex AI section, go to the Datasets page.
Click Create in the button bar to create a new dataset.
Structured_AutoML_Tutorialfor the dataset name and select the Tabular tab.
Leave the Region set to us-central1.
Click Create to create the dataset.
For Select a data source, click Select CSV files from Cloud Storage and enter
cloud-ml-tables-data/bank-marketing.csvfor the Cloud Storage path.
The Analyze pane opens.
Click Generate statistics to generate statistics for the dataset.
When the statistics are generated, you can click on any feature to see more details about the data for that feature.
Train an AutoML classification model
Click Train new model.
In the Train new model pane, make sure the dataset you created previously is selected for the Dataset field and select Classification for the objective.
Confirm that the AutoML training method is selected, and click Continue.
Select Deposit for the target column and click Continue.
The list of columns is displayed, with the transformation that will be used for each feature.
Click Continue to display the Compute and pricing panel, and enter
1for the training budget.
Click Start training.
The training budget determines actual training time, but the time to complete training includes other activities, so the entire process can take longer than one hour. When the model finishes training, it is displayed in the model tab as a live link, with a green checkmark status icon.
Follow the next page of this tutorial to deploy your model and request a prediction.