Summary

In this chapter, we learned about Vertex AI Workbench, a managed platform for launching the Jupyter Notebook application on Google Cloud. We talked about the benefits of having notebooks in a cloud-based environment as compared to a local environment. Having Jupyter Notebook in the cloud makes it perfect for collaboration, scaling, adding security, and launching long-running jobs. We also discussed additional features of Vertex AI Workbench that are pretty useful while working on different aspects of ML project development.

After reading this chapter, we should be able to successfully deploy, manage, and use Jupyter Notebooks on the Vertex AI platform for our ML development needs. As we understand the difference between managed and user-managed notebook instances, we should be in good shape to choose the best solution for our development needs. We should also be able to create custom Docker container-based notebooks if required. Most importantly, we should now be able to...