Google Cloud Professional Machine Learning Engineer — Question 245

You are working on a prototype of a text classification model in a managed Vertex AI Workbench notebook. You want to quickly experiment with tokenizing text by using a Natural Language Toolkit (NLTK) library. How should you add the library to your Jupyter kernel?

Answer options

• A. Install the NLTK library from a terminal by using the pip install nltk command.
• B. Write a custom Dataflow job that uses NLTK to tokenize your text and saves the output to Cloud Storage.
• C. Create a new Vertex AI Workbench notebook with a custom image that includes the NLTK library.
• D. Install the NLTK library from a Jupyter cell by using the !pip install nltk --user command.

Correct answer: D

Explanation

The correct answer is D because it allows for the installation of the NLTK library directly within the Jupyter notebook environment, making it quick and efficient for experimentation. Option A requires terminal access and does not directly integrate into the Jupyter kernel. Option B involves additional complexity with Cloud Storage, and option C is unnecessary for a simple library installation when it can be done directly in the notebook.