Each of the tutorials presented here walks you through a specific artificial intelligence (AI) workflow, created to represent the most common tasks and to illustrate the capabilities of Vertex AI. Choose the tutorial that best matches your data type and AI task. After following the tutorial, you can use the patterns that you have learned to solve your own AI problem. Vertex AI offers Google Cloud console tutorials and Jupyter notebook tutorials that use the Python SDK. You can open a notebook tutorial directly in Colab, download the notebook to your preferred environment, or open the notebook tutorial in Vertex AI Workbench.
Train a classification model for tabular data
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Create a Vertex AI dataset from tabular data, and then train a classification model with AutoML. Deploy the model to an endpoint and make online predictions.
Google Cloud console: You can choose tutorial guides with step-by-step instructions for the Google Cloud console.
Jupyter notebook: You can choose to run this tutorial as a Jupyter notebook. |
Train a regression model for tabular data
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Create a Vertex AI dataset from tabular data, and then train a regression model with AutoML. Deploy the model to an endpoint and make online predictions or make predictions in batch format.
Jupyter notebook: You can choose to run this tutorial and make online predictions using
a Jupyter notebook.
Jupyter notebook: You can choose to run this tutorial and make batch predictions using
a Jupyter notebook. |
Train a time-series forecasting model for tabular data
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Create a Vertex AI dataset from tabular data, and then train a forecasting model with AutoML. Make predictions in batch format.
Jupyter notebook: You can choose to run this tutorial as a Jupyter notebook. |
Train a classification model for text data
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Create a Vertex AI dataset for text data, and then train a classification model with AutoML. Deploy the model to an endpoint and make online predictions.
Google Cloud console: You can choose tutorial guides with step-by-step instructions for the Google Cloud console.
Jupyter notebook: You can choose to run this tutorial as a Jupyter notebook. |
Train a classification model for image data
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Create a Vertex AI dataset for image data, and then train a classification model with AutoML. Deploy the model to an endpoint and make online predictions.
Google Cloud console: You can choose tutorial guides with step-by-step instructions for the Google Cloud console. |
Train a classification model for video data
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Create a Vertex AI dataset for video data, and then train a classification model with AutoML. Make predictions in batch format.
Google Cloud console: You can choose tutorial guides with step-by-step instructions for the Google Cloud console.
Jupyter notebook: You can choose to run this tutorial as a Jupyter notebook. |
How to open a notebook in Vertex AI Workbench
To open a notebook tutorial in a Vertex AI Workbench instance:
- Click the Vertex AI Workbench link in the notebook list. The link opens the Vertex AI Workbench console.
- In the Deploy to notebook screen, type a name for your new Vertex AI Workbench instance and click Create.
- In the Ready to open notebook dialog that appears after the instance starts, click Open.
- On the Confirm deployment to notebook server page, select Confirm.
- Before running the notebook, select Kernel > Restart Kernel and Clear all Outputs.
What's next
- View the full list of Vertex AI notebook tutorials.
- Learn more about model training.