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tfidf_matrix[item_index].toarray()[0] * rating Step 2: Collaborative Filtering Recommendations Next, we’ll use collaborative filtering to generate a set of recommendations based on user behavior. We can use the user’s past interactions to find users with similar preferences and recommend items that