You have recently developed a new ML model in a Jupyter notebook.

1. Create an instance of the CustomTrainingJob class with the Vertex AI SDK to train your model.

2. Using the Notebooks API, create a scheduled execution to run the training code weekly.

1. Create an instance of the CustomJob class with the Vertex AI SDK to train your model.

2. Use the Metadata API to register your model as a model artifact.

3. Using the Notebooks API, create a scheduled execution to run the training code weekly.

1. Create a managed pipeline in Vertex Al Pipelines to train your model by using a Vertex Al CustomTrainingJoOp component.

2. Use the ModelUploadOp component to upload your model to Vertex Al Model Registry.

3. Use Cloud Scheduler and Cloud Functions to run the Vertex Al pipeline weekly.

1. Create a managed pipeline in Vertex Al Pipelines to train your model using a Vertex Al HyperParameterTuningJobRunOp component.

2. Use the ModelUploadOp component to upload your model to Vertex Al Model Registry.

3. Use Cloud Scheduler and Cloud Functions to run the Vertex Al pipeline weekly.