GCP ML Engineer Practice Questions - Google Cloud Professional Machine Learning Engineer Exam - Variant 2

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A retail company wants to build a product recommendation engine using their existing BigQuery sales data. They have limited ML expertise on their team. Which GCP approach best fits this scenario?

Train a custom TensorFlow model on Vertex AI Training Use BigQuery ML to create a matrix factorization model Deploy a pre-trained model from Model Garden Build a custom pipeline with Kubeflow on GKE

Correct Answer:

Use BigQuery ML to create a matrix factorization model

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