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In this video tutorial, Amun, a data scientist, discusses the importance of cleaning text data for natural language processing. Cleaning data is a fundamental step in the data science pipeline, and while there are techniques like missing value and outlier treatment for numerical data, text data requires different cleaning techniques. The two main categories of text cleaning techniques are basic and advanced cleaning. Basic cleaning is essential and includes tasks like spell-checking, while advanced cleaning may be necessary in some cases. The video will cover these techniques in detail to help you effectively clean text data for analysis.
