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Answer: Train a classification Vertex AutoML model.
The correct answer is B. Using Vertex AutoML model allows you to complete all steps of the machine learning pipeline without writing any code. Vertex AutoML handles exploratory data analysis, feature selection, model building, training, hyperparameter tuning, and serving seamlessly and is specifically designed to work with structured data in BigQuery. Other options (A, C, and D) require writing code in TensorFlow, BigQuery ML, or scikit-learn respectively.
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You are tasked with building recurring classification workflows over several structured datasets currently stored in BigQuery. Your objective includes performing several machine learning steps such as exploratory data analysis, feature selection, model building, training, hyperparameter tuning, and serving, all without writing any code. Given these requirements, what should you do?
A
Train a TensorFlow model on Vertex AI.
B
Train a classification Vertex AutoML model.
C
Run a logistic regression job on BigQuery ML.
D
Use scikit-learn in Vertex AI Workbench user-managed notebooks with pandas library.