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Google Cloud Certified Professional Machine Learning Engineer · Google Cloud
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This is a time-dependent prediction problem. For AutoML Tables (Vertex AI Tabular), Google's recommended practice is: Provide a Time column that represents the temporal ordering of examples. Let AutoML perform its built-in time-aware data split. Use older data for training and newer data for validation/testing. This prevents data leakage where future information accidentally influences training.
Why Option C is correct: AutoML is specifically designed to handle time-series forecasting and temporal data. By designating a specific column as the Time column, the service automatically understands the chronological order of the records. It will perform a time-based split—ensuring that the training set consists of older data, and the validation and testing sets consist of more recent data. This mimics real-world scenarios where you use historical data to predict future outcomes, avoiding the mistake of using "future" information to predict the "past."
We are using AutoML to reduce the manual effort, which is important for Google.