Topic 1 Question 293
You are developing a batch process that will train a custom model and perform predictions. You need to be able to show lineage for both your model and the batch predictions. What should you do?
- Upload your dataset to BigQuery.
- Use a Vertex AI custom training job to train your model.
- Generate predictions by using Vertex AI SDK custom prediction routines.
- Use Vertex AI Experiments to evaluate model performance during training.
- Register your model in Vertex AI Model Registry.
- Generate batch predictions in Vertex AI.
- Create a Vertex AI managed dataset.
- Use a Vertex AI training pipeline to train your model.
- Generate batch predictions in Vertex AI.
- Use a Vertex AI Pipelines custom training job component to train your model.
- Generate predictions by using a Vertex AI Pipelines model batch predict component.
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コメント(2)
- 正解だと思う選択肢: D
A (Vertex AI custom training job and custom prediction routines): This approach lacks the built-in lineage tracking capabilities of Vertex AI Pipelines. You would need to implement custom mechanisms to log and track the relevant metadata. B (Vertex AI Experiments and Model Registry): These are valuable tools, but they focus more on experiment management and model versioning. They don't provide the same level of workflow and lineage tracking as pipelines. C (Vertex AI managed dataset and batch prediction): While helpful, this doesn't provide the same level of granularity and traceability as pipelines for tracking the complete lineage, especially the training process.
👍 3AB_C2024/11/27 - 正解だと思う選択肢: D
A: Vertex AI SDK custom prediction routines do not provide lineage B: it focuses more on experiments and does not provide lineage as Vertex AI pipelines C: might appear correct, especially by the use of managed dataset, but a generic Vertex AI training pipeline does not provide lineage for a custom model as much as a custom training job component of D.
👍 1MarcoPellegrino2025/01/14
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