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Learn about Natural Language Processing fundamentals in this comprehensive lecture covering Part of Speech (POS) tagging, Named Entity Recognition (NER), and Hidden Markov Models (HMM). Explore how POS tagging helps identify grammatical components in text, discover techniques for recognizing and classifying named entities like people, organizations, and locations, and understand the mathematical principles behind Hidden Markov Models used in sequential data analysis. Access accompanying slides that provide detailed explanations, examples, and visual aids to reinforce understanding of these essential NLP concepts and their practical applications in text analysis and processing.
