Google Professional Machine Learning Engineer exam dumps

Google Professional Machine Learning Engineer practice question 109 of 522

Professional Machine Learning Engineer. Professional level, Google Cloud. Free question with the correct answer and a full explanation.

Google Professional Machine Learning Engineer Question 109

Select 3Google Cloud Platform

You are tasked with building a machine learning model using Vertex AI to predict customer churn. The team has provided the raw data as a series of CSV files stored in a Google Cloud Storage bucket. Before training the model, you need to prepare and manage the dataset in Vertex AI. Which of the following steps should you take to properly manage the dataset in Vertex AI?

  1. A

    Import the CSV files into a Vertex AI Dataset by specifying the GCS bucket path.

  2. B

    Manually preprocess the data on your local machine before uploading it to Vertex AI.

  3. C

    Use Vertex AI to split the dataset into training, validation, and test sets.

  4. D

    Export the Vertex AI Dataset to BigQuery for advanced SQL-based preprocessing.

  5. E

    Apply data labeling within Vertex AI if your dataset requires labeling.

Show answer and explanation

Correct answers: A, C, E

Explanation

To properly manage datasets in Vertex AI, you should start by importing the data from Google Cloud Storage into a Vertex AI Dataset. From there, you can utilize built-in tools to split the dataset for training, validation, and testing. If the dataset requires labeling, Vertex AI provides integrated labeling services to streamline this process. While external preprocessing tools like BigQuery or manual local preprocessing are options, they are not necessary steps in the Vertex AI workflow.

  • A. Correct.

    Correct: Vertex AI allows you to import CSV files directly from a GCS bucket into a Dataset, which is the first step in managing data for machine learning workflows.

  • B. Incorrect.

    Incorrect: While manual preprocessing is possible, it is not necessary to preprocess data locally when using Vertex AI. Vertex AI provides tools for preprocessing and managing datasets directly within the platform.

  • C. Correct.

    Correct: Vertex AI provides functionality to split datasets into training, validation, and test sets, which is a key part of preparing data for machine learning models.

  • D. Incorrect.

    Incorrect: While exporting data to BigQuery is possible, it is not required as part of the dataset management process in Vertex AI. Many preprocessing steps can be handled directly within Vertex AI.

  • E. Correct.

    Correct: If your dataset requires labeling, Vertex AI provides integrated data labeling services to annotate your data for supervised learning tasks.

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