Vertex AI TensorBoard custom training with custom container: Notebook

In this tutorial, you learn how to create a custom training job using custom containers, and monitor your training process on Vertex AI TensorBoard in near real time.

Notebook: Create custom training jobs using custom containers

To see an example of tensorboard custom training with custom container, run the "Vertex AI TensorBoard custom training with custom container" Jupyter notebook in one of the following environments:

Open in Colab | Open in Colab Enterprise | Open in Vertex AI Workbench user-managed notebooks | View on GitHub

This tutorial uses the following Google Cloud ML services and resources:

• Vertex AI training
• Vertex AI TensorBoard

The steps performed include:

• Create a Docker repository and config.
• Create a custom container image with your customized training code.
• Set up a service account and Cloud Storage buckets.
• Create and launch your custom training job with your custom container.

Relevant content

• Vertex AI TensorBoard
• Custom training