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Answer: Configure AutoML Tables to perform the classification task.
The correct answer is A: Configure AutoML Tables to perform the classification task. The key requirement mentioned in the question is to accomplish the classification task without writing any code. AutoML Tables allows you to automatically build and deploy machine learning models on structured data through a user-friendly, no-code interface. This satisfies the need for exploratory data analysis, feature selection, model building, training, hyperparameter tuning, and serving, all without requiring manual coding. On the other hand, BigQuery ML, AI Platform Notebooks, and AI Platform for hyperparameter tuning would require some level of coding, which does not meet the requirement specified in the question.
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You are tasked with developing classification workflows using several structured datasets that are currently stored in BigQuery. These workflows need to be executed multiple times. You aim to accomplish the following steps without writing any code: exploratory data analysis, feature selection, model building, training, hyperparameter tuning, and eventually serving the model. Given these requirements, what should you do?
A
Configure AutoML Tables to perform the classification task.
B
Run a BigQuery ML task to perform logistic regression for the classification.
C
Use AI Platform Notebooks to run the classification model with pandas library.
D
Use AI Platform to run the classification model job configured for hyperparameter tuning.