Google Professional Machine Learning Engineer
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In the context of developing a machine learning model for a financial services company that must comply with strict regulatory requirements, at which stage in the machine learning pipeline is hyperparameter tuning most effectively conducted to ensure both model performance and compliance? Choose the best option.
In the context of developing a machine learning model for a financial services company that must comply with strict regulatory requirements, at which stage in the machine learning pipeline is hyperparameter tuning most effectively conducted to ensure both model performance and compliance? Choose the best option.
Real Exam
A
After model deployment, to continuously improve the model based on real-world performance data.
6.1%
B
Before training the model, to optimize the model's performance and ensure it meets regulatory standards from the outset.
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