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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #274
You are developing a custom TensorFlow classification model based on tabular data. Your raw data is stored in BigQuery. contains hundreds of millions of rows, and includes both categorical and numeric
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Submitted by kevin_r· Apr 18, 2026Data processing and feature engineering
Question
You are developing a custom TensorFlow classification model based on tabular data. Your raw data is stored in BigQuery. contains hundreds of millions of rows, and includes both categorical and numerical features. You need to use a MaxMin scaler on some numerical features, and apply a one-hot encoding to some categorical features such as SKU names. Your model will be trained over multiple epochs. You want to minimize the effort and cost of your solution. What should you do?
Options
- A
- Write a SQL query to create a separate lookup table to scale the numerical features.
- B
- Use BigQuery to scale the numerical features.
- C
- Use TFX components with Dataflow to encode the text features and scale the numerical
- D
- Write a SQL query to create a separate lookup table to scale the numerical features.
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Topics
#Feature Engineering#Data Preprocessing#TensorFlow Extended (TFX)#Google Cloud Dataflow