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In this video tutorial, Amun, a data scientist, discusses the cleaning techniques for natural language processing. Cleaning the data is a fundamental step in the data science pipeline, and while techniques like missing value treatment and outlier treatment are used for numeric data, text data requires a different set of cleaning techniques. The cleaning techniques for text data can be categorized into basic cleaning and advanced cleaning. It is important to understand the basic cleaning techniques before moving on to advanced cleaning.