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In this video tutorial, Amun, a data scientist, discusses the importance of cleaning textual data for natural language processing. He highlights that cleaning data is a fundamental step in the data science pipeline, just like treating missing values and outliers in numerical data. Text data requires specific cleaning techniques, which can be classified into basic and advanced cleaning methods. Amun emphasizes the importance of understanding and implementing both types of cleaning techniques for effective data processing.