Natural Language Processing: POS Tagging, Named Entity Recognition, and Hidden Markov Models

Learn about natural language processing fundamentals in this lecture covering linguistic structure prediction, part-of-speech (POS) tagging, and named entity recognition (NER). Begin with the motivations behind linguistic structure prediction before diving into POS tags and their implementation in text analysis. Explore the concept of named entities and how to identify them through NER techniques. Conclude with an introduction to hidden Markov models and their applications in language processing tasks. Master essential NLP concepts through clear explanations and practical examples over the course of 70 minutes.