LAB | Run Your Machine Learning Code in Google Cloud Vertex AI Workbench

Prerequisites

• Basic experience with Python and machine learning
• Access to a Google Cloud account with Vertex AI permissions

Objective

Learn how to run machine learning code using Vertex AI Workbench notebooks on Google Cloud Platform without managing underlying infrastructure.

Instructions

1. Access Google Cloud Console and navigate to Vertex AI Workbench.

2. Follow the instructions to create a new Vertex AI Workbench instance:

   • Select a CPU-based environment (or GPU if desired).
   • Launch the JupyterLab interface.

3. Inside the JupyterLab environment:

   • Open a new notebook.
   • Prepare and run your ML script to train and make predictions.
   • You may reuse previous ML code or create new machine learning code.

4. Shut down the Vertex AI Workbench instance when done to avoid unnecessary charges.

Important

For complete setup and usage details, refer to the official documentation:
https://cloud.google.com/vertex-ai/docs/workbench/instances/introduction

Deliverable

• Screenshot of the Instance on Goggle VertexAI.
• Screenshot of the notebook with the output of the prediction printed.

Submission

Upon completion, add your deliverables to git. Then commit git and push your branch to the remote.