Google Professional Machine Learning Engineer
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Ultimate access to all questions.
You are a data scientist working for a retail company. Your goal is to build a predictive model to estimate the probability of customer churn, i.e., the likelihood that a customer will stop purchasing from the company. The results must be interpretable so that the insights can guide marketing teams to develop targeted campaigns aimed at retaining at-risk customers. What should you do to achieve this?
A
Build a random forest regression model in a Vertex AI Workbench notebook instance. Configure the model to generate feature importances after the model is trained.
B
Build an AutoML tabular regression model. Configure the model to generate explanations when it makes predictions.
C
Build a custom TensorFlow neural network by using Vertex AI custom training. Configure the model to generate explanations when it makes predictions.
D
Build a random forest classification model in a Vertex AI Workbench notebook instance. Configure the model to generate feature importances after the model is trained.