Google Professional Machine Learning Engineer
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You are part of a team responsible for server maintenance in a large data center. Your management is requesting a predictive maintenance solution to detect potential server failures using monitoring data. However, the incident data has not been labeled yet, making it challenging to train a machine learning model immediately. What should be your first step in this situation?
A
Train a time-series model to predict the machines’ performance values. Configure an alert if a machine’s actual performance values significantly differ from the predicted performance values.
B
Develop a simple heuristic (e.g., based on z-score) to label the machines’ historical performance data. Use this heuristic to monitor server performance in real time.
C
Develop a simple heuristic (e.g., based on z-score) to label the machines’ historical performance data. Train a model to predict anomalies based on this labeled dataset.
D
Hire a team of qualified analysts to review and label the machines’ historical performance data. Train a model based on this manually labeled dataset.