Named Entity Recognition (NER)

Named Entity Recognition (NER) focuses on identifying and classifying important entities in unstructured text such as names of people, organizations, locations, dates, and other key information. It enables systems to convert raw text into structured, meaningful data for downstream NLP applications. This training explains how NER works using rule-based, statistical, and deep learning approaches including transformer-based models. It also covers annotation schemes like BIO tagging, feature extraction, and contextual embeddings. You will learn how organizations use NER in search engines, chatbots, document processing, and information extraction systems. The course also highlights best practices for improving accuracy and handling domain-specific entity recognition challenges.