Google Professional Machine Learning Engineer
Get started today
Ultimate access to all questions.
You are tasked with evaluating a medium-sized (~10 GB) BigQuery table that will serve as the dataset for an upcoming machine learning project. The primary objectives are to quickly assess the data's suitability for model development with maximum flexibility and to produce a comprehensive one-time report for your team of ML engineers. This report should include detailed visualizations of data distributions and sophisticated statistical analyses to inform the model development process. Considering the need for flexibility, depth of analysis, and ease of sharing insights with the team, which of the following approaches would best achieve these goals? (Choose two correct options if option E is available, otherwise choose one.)
You are tasked with evaluating a medium-sized (~10 GB) BigQuery table that will serve as the dataset for an upcoming machine learning project. The primary objectives are to quickly assess the data's suitability for model development with maximum flexibility and to produce a comprehensive one-time report for your team of ML engineers. This report should include detailed visualizations of data distributions and sophisticated statistical analyses to inform the model development process. Considering the need for flexibility, depth of analysis, and ease of sharing insights with the team, which of the following approaches would best achieve these goals? (Choose two correct options if option E is available, otherwise choose one.)