Google Cloud Certified Professional Machine Learning Engineer Practice Mode

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose A1

  A : It is the simplest answer. The others seem to be trying to solve feature selection again but the problem is not feature selection but input data drift. Rethinking features is not needed, simple monitoring and readjusting weights is needed.

• Chose A1

  A) Monitor the model and set alerts

• Chose A2

  When the distribution of input data changes, the model may not perform as well as it did during training. It is important to monitor the performance of the model in production and identify any changes in the distribution of input data. By creating alerts to monitor for skew, you can detect when the input data distribution has changed and take action to retrain the model using more recent data that reflects the new distribution. This will help ensure that the model continues to perform well in production.