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You are working on a prototype of a text classification model that aims to categorize textual data into predefined categories. To facilitate this, you are using a managed Vertex AI Workbench notebook. As part of your preprocessing steps, you want to quickly experiment with tokenizing text using the Natural Language Toolkit (NLTK) library. How should you add the NLTK library to your Jupyter kernel within this managed environment?
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.