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This lecture introduces text classification and the Naive Bayes algorithm, a key method. Examples of text classification applications are discussed, using a spam email as an example. Features indicating spam include typos, unusual language, lack of personalization, undisclosed recipients, and suspicious URLs. These features can be combined for effective classification.