When preparing text data for machine learning, what is the purpose of tokenization?

When preparing text data for machine

Multiple choice — select the best answer

ARemoving outliers from numeric data
BConverting categorical variables into numeric representations
CBreaking text into smaller units like words or phrases that can be processed by algorithms
DEncrypting sensitive information in the text

✓ Correct answer: C. Breaking text into smaller units like words or phrases that can be processed by algorithms Tokenization is the process of breaking down text into smaller units (tokens) such as words, phrases, or characters. This is a fundamental preprocessing step for text data, as it converts raw text into discrete elements that can be processed by machine learning algorithms.

.q-expl{display:block!important}.q-opt[data-idx="2"]{border-color:#16a34a;background:#f0fdf4}.q-opt[data-idx="2"] .oltr{background:#16a34a;color:#fff}.q-opt{cursor:default!important;pointer-events:none}

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