Topic 1 Question 199

Professional Machine Learning Engineer

Topic 1 Question 199
You are developing a process for training and running your custom model in production. You need to be able to show lineage for your model and predictions. What should you do?
- 1. Create a Vertex AI managed dataset.
  2. Use a Vertex AI training pipeline to train your model.
  3. Generate batch predictions in Vertex AI.
- 1. Use a Vertex AI Pipelines custom training job component to tram your model.
  2. Generate predictions by using a Vertex AI Pipelines model batch predict component.
- 1. Upload your dataset to BigQuery.
  2. Use a Vertex AI custom training job to train your model.
  3. Generate predictions by using Vertex Al SDK custom prediction routines.
- 1. Use Vertex AI Experiments to train your model.
  2. Register your model in Vertex AI Model Registry.
  3. Generate batch predictions in Vertex AI.
ユーザの投票
コメント(17)
- 正解だと思う選択肢: D
  My Answer: D
  
  According with: https://cloud.google.com/vertex-ai/docs/experiments/intro-vertex-ai-experiments
  
  “Vertex AI Experiments is a tool that helps you track and analyze different model architectures, hyperparameters, and training environments, letting you track the steps, inputs, and outputs of an experiment run. Vertex AI Experiments can also evaluate how your model performed in aggregate, against test datasets, and during the training run. You can then use this information to select the best model for your particular use case.”.
  
  Considering that both options A and B could demonstrate some form of lineage, I believe option D is the most suitable. The text explicitly states "show lineage for your model and predictions," which aligns perfectly with the functionality provided by Vertex AI Experiments.
  
  👍 7
  guilhermebutzke2024/02/13
- 正解だと思う選択肢: B
  Vertex AI Pipelines are suited to do artifact lineage https://cloud.google.com/vertex-ai/docs/pipelines/lineage Experiments can do it also, but their main goal is to "track and analyze different model architectures, hyperparameters, and training environments"
  
  👍 6
  edoo2024/03/08
- 正解だと思う選択肢: B
  B) REF https://cloud.google.com/vertex-ai/docs/pipelines/lineage
  
  Track the lineage of pipeline artifacts
  
  When you run a pipeline using Vertex AI Pipelines, the artifacts and parameters of your pipeline run are stored using Vertex ML Metadata. Vertex ML Metadata makes it easier to analyze the lineage of your pipeline's artifacts, by saving you the difficulty of keeping track of your pipeline's metadata.
  
  An artifact's lineage includes all the factors that contributed to its creation, as well as artifacts and metadata that are derived from this artifact. For example, a model's lineage could include the following:
  
  The training, test, and evaluation data used to create the model. The hyperparameters used during model training. Metadata recorded from the training and evaluation process, such as the model's accuracy. Artifacts that descend from this model, such as the results of batch predictions.
  
  👍 5
  ddogg2024/02/01
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