In the context of TensorFlow on GCP, what is TensorFlow Data Validation used for?
- TensorFlow Data Validation is used to analyze and validate training data to identify anomalies, inconsistencies, and data quality issues.
- TensorFlow Data Validation is primarily used for model inference and evaluation, ensuring that deployed models perform accurately on new data.
- TensorFlow Data Validation facilitates real-time data streaming and processing for continuous model training and updating.
- TensorFlow Data Validation provides tools for model interpretation and explainability, helping stakeholders understand how models make predictions.
Understanding the role of TensorFlow Data Validation in the ML pipeline on Google Cloud Platform is crucial for ensuring the quality and reliability of machine learning models deployed in production environments.
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