Topic 1 Question 93
You have been asked to build a model using a dataset that is stored in a medium-sized (~10 GB) BigQuery table. You need to quickly determine whether this data is suitable for model development. You want to create a one-time report that includes both informative visualizations of data distributions and more sophisticated statistical analyses to share with other ML engineers on your team. You require maximum flexibility to create your report. What should you do?
Use Vertex AI Workbench user-managed notebooks to generate the report.
Use the Google Data Studio to create the report.
Use the output from TensorFlow Data Validation on Dataflow to generate the report.
Use Dataprep to create the report.
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コメント(17)
- 正解だと思う選択肢: B
B BQ is great for analyzing and visualizing data (integrating with Data Studio)
👍 3hiromi2022/12/19 - 正解だと思う選択肢: B
A. User-managed --> non quickly. C. No Tensorflow D. Analysis, not preparation for analysis --> no Dataprep. It seems that Data Studio is the way to go. The answer is B.
👍 2ares812022/12/14 - 正解だと思う選択肢: A
I think it's A.One time report containing real datasets STATISTICAL measurements to tell if the data is suitable for model development. Target audience is also other ML engineers. Getting a whole report of exactly this with TFDV/Facets is like two lines of code: https://www.tensorflow.org/tfx/data_validation/get_started
A similar data studio report for this would take lots of time and work, and there would be no benefit from reuseability since task was a one-time job.
👍 2JamesDoe2023/03/28
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