Professional Machine Learning Engineer

By Google · Question Mode

QuestionQ17

Automating and orchestrating ML pipelines

You created a Vertex AI pipeline with two steps. The first step preprocesses 10 TB of data, completes in about 1 hour, and saves the result to a Cloud Storage bucket. The second step uses the processed data to train a model.

You need to update the model’s code so that you can test different algorithms. You want to reduce pipeline execution time and cost while minimizing changes to the pipeline. What should you do?

Explanation

Vertex AI Pipelines can reuse the output of an unchanged preprocessing task from execution cache, avoiding the repeated processing of 10 TB of data. Disabling caching for model training ensures that training runs again for each updated algorithm or code version. Configure execution caching

Learn more

Community Discussion

No comments yet. Be the first to start the discussion!