MLS-C01 · Question #101
MLS-C01 Question #101: Real Exam Question with Answer & Explanation
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Question
A manufacturer of car engines collects data from cars as they are being driven. The data collected includes timestamp, engine temperature, rotations per minute (RPM), and other sensor readings. The company wants to predict when an engine is going to have a problem, so it can notify drivers in advance to get engine maintenance. The engine data is loaded into a data lake for training. Which is the MOST suitable predictive model that can be deployed into production?
Options
- AAdd labels over time to indicate which engine faults occur at what time in the future to turn this
- BThis data requires an unsupervised learning algorithm.
- CAdd labels over time to indicate which engine faults occur at what time in the future to turn this
- DThis data is already formulated as a time series.
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