You are conducting experiments with a built-in gcp video
ml-engineer-pro video for you are conducting experiments with a built-in distributed XGBoost model in Vertex AI Workbench user-managed notebooks. To split your
Full Certification Question
You are conducting experiments with a built-in distributed XGBoost model in Vertex AI Workbench user-managed notebooks. To split your data into training and validation sets, you use the following BigQuery queries: CREATE OR REPLACE TABLE ‘ myproject . mydataset . training ‘ AS ( SELECT * FROM ‘ myproject . mydataset . mytable ‘ WHERE RAND () <= 0.8 ); CREATE OR REPLACE TABLE ‘ myproject . mydataset . validation ‘ AS ( SELECT * FROM ‘ myproject . mydataset . mytable ‘ WHERE RAND () <= 0.2 ); After training the model, you achieve an area under the receiver operating characteristic curve (AUC ROC) value of 0.8. However, after deploying the model to production, you observe that the model's performance has dropped to an AUC ROC value of 0.65. What is the most likely problem occurring?