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The assignment for Natural Language Processing at Bahria University requires students to preprocess a dataset for modeling by performing tokenization, stop word removal, and stemming or lemmatization, with explanations and examples. Additionally, students must apply Bag of Words and TF-IDF feature extraction techniques and analyze the sparse vector issue in both representations. A comparison of the two methods is also required to determine which is superior and the reasoning behind it.

Author

usamahydr2838

Language

EN