Natural Language Processing (NLP) is one of the key domains in AI, where the primary challenge lies in converting unstructured text into structured formats suitable for machine learning models. This chapter covers essential NLP preprocessing steps such as tokenization, stopword removal, stemming, lemmatization, and vectorization. By mastering these techniques, you can effectively preprocess text data for various NLP tasks like sentiment analysis, machine translation, and text generation.
TaiwoJalupon, I. & Zakariyya, A. (2025). Artificial Intelligence: A Comprehensive Guide to Preprocessing Across Modalities. Afribary. Retrieved from https://tracking.afribary.com/works/artificial-intelligence-a-comprehensive-guide-to-preprocessing-across-modalities
TaiwoJalupon, Iman, and Amina Zakariyya "Artificial Intelligence: A Comprehensive Guide to Preprocessing Across Modalities" Afribary. Afribary, 21 Sep. 2025, https://tracking.afribary.com/works/artificial-intelligence-a-comprehensive-guide-to-preprocessing-across-modalities. Accessed 15 Oct. 2025.
TaiwoJalupon, Iman, and Amina Zakariyya . "Artificial Intelligence: A Comprehensive Guide to Preprocessing Across Modalities". Afribary, Afribary, 21 Sep. 2025. Web. 15 Oct. 2025. < https://tracking.afribary.com/works/artificial-intelligence-a-comprehensive-guide-to-preprocessing-across-modalities >.
TaiwoJalupon, Iman and Amina Zakariyya . "Artificial Intelligence: A Comprehensive Guide to Preprocessing Across Modalities" Afribary (2025). Accessed October 15, 2025. https://tracking.afribary.com/works/artificial-intelligence-a-comprehensive-guide-to-preprocessing-across-modalities