Spam filter: collect 10k labeled emails, train a classifier, deploy; new emails get spam/not-spam predictions. The model learned patterns (free money, urgency) from data, not hand-coded rules. When spammers adapt, retrain on new labels. This data-driven loop is ML's essence.