Google Professional Machine Learning Engineer
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Ultimate access to all questions.
You are working on a machine learning model that relies on data from a third-party data broker. However, the data broker has a history of making unannounced formatting changes to the data, which could disrupt your model training pipeline. To mitigate this risk and make your pipeline more robust, what should you do?
A
Use TensorFlow Data Validation to detect and flag schema anomalies.
B
Use TensorFlow Transform to create a preprocessing component that will normalize data to the expected distribution, and replace values that don’t match the schema with 0.
C
Use tf.math to analyze the data, compute summary statistics, and flag statistical anomalies.
D
Use custom TensorFlow functions at the start of your model training to detect and flag known formatting errors.