Topic 1 Question 156
You need to build classification workflows over several structured datasets currently stored in BigQuery. Because you will be performing the classification several times, you want to complete the following steps without writing code: exploratory data analysis, feature selection, model building, training, and hyperparameter tuning and serving. What should you do?
Train a TensorFlow model on Vertex AI.
Train a classification Vertex AutoML model.
Run a logistic regression job on BigQuery ML.
Use scikit-learn in Vertex AI Workbench user-managed notebooks with pandas library.
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コメント(4)
- 正解だと思う選択肢: B
B "without writing code"
👍 1powerby352023/07/13 - 正解だと思う選択肢: B
A and D would require writing code. C. would also imply some “code writing” in BigQuery ML
I would go with B.
👍 1Nxtgen2023/08/23 B is correct. A and D imply writing code in TF and Sklearn respectively. C is writing BQML code for logistic regression as well. Furthermore, how would you do the EDA and feature selection etc. without writing code? AutoML is THE codeless solution automating all the steps mentioned above. https://cloud.google.com/automl?hl=en
👍 1bugger1232023/12/07
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