Professional-Machine-Learning-Engineer Exam Dumps | One of your models is trained using data provided by a third-party data broker. The data broker does

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Question 139

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Question 139/139

One of your models is trained using data provided by a third-party data broker. The data broker does not reliably notify you of formatting changes in the data. You want to make your model training pipeline more robust to issues like this. 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.

Correct Answer: A

TensorFlow Data Validation (TFDV) is a library that helps you understand, validate, and monitor your data for machine learning. It can automatically detect and report schema anomalies, such as missing features, new features, or different data types, in your data. It can also generate descriptive statistics and data visualizations to help you explore and debug your data. TFDV can be integrated with your model training pipeline to ensure data quality and consistency throughout the machine learning lifecycle. References:
* TensorFlow Data Validation
* Data Validation | TensorFlow
* Data Validation | Machine Learning Crash Course | Google Developers

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