Named Entity Recognition (NER) focuses on identifying and classifying key information entities within unstructured text such as names of people, organizations, locations, dates, and more. It enables systems to extract structured insights from large volumes of text data. This training explains how NER works using rule-based, statistical, and deep learning approaches. It also covers techniques such as tokenization, tagging schemes (BIO format), and contextual embeddings. You will learn how NER is applied in search engines, chatbots, information retrieval, and document processing. The course also highlights best practices for improving accuracy and handling domain-specific entities.
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