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This lecture introduces text classification and the Naive Bayes algorithm, essential for text classification. Examples of text classification applications are discussed, such as identifying spam emails. Features like misspellings, unusual subject headers, lack of personalization, and suspicious URLs can help identify spam. Each feature can be combined to accurately classify text.