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What is the primary purpose of tokenization in natural language processing (NLP)?
To translate text into another language.
To summarize large documents.
To break down text into smaller units for analysis.
Which of the following techniques is used to determine the importance of words in a document within the context of a larger collection of documents?
Naïve Bayes
TF-IDF (Term Frequency-Inverse Document Frequency)
Word2Vec
Which of the following best describes the role of embeddings in natural language processing (NLP)?
They visualize text data in two-dimensional space for easier interpretation.
They summarize large text corpora into short, meaningful sentences.
They convert language tokens into vectors that capture semantic relationships.
You must answer all questions before checking your work.
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