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In tip 29 of the YouTube tutorial, the speaker explains how to vectorize two text columns using a column transformer. Since most preprocessing steps in Scikit-learn expect 2D objects, the count vectorizer, which encodes text data in a bag of words format, can only accept 1D objects. By passing the vectorizer twice in the column transformer, you can create separate vocabularies for each text column and include both in the resulting dataset for model training. This workaround allows you to effectively preprocess multiple text columns for machine learning tasks.