Natural Language Processing (NLP) encompasses a variety of tasks, each with distinct methodologies and applications, including Named Entity Recognition (NER), sentiment analysis, classification, machine translation, summarisation, and information extraction. These tasks underpin numerous real-world applications, from virtual assistants to automated content analysis. This essay explores these core NLP tasks, their
The transformative potential of Natural Language Processing (NLP), as a cornerstone of artificial intelligence, lies in its ability to enable machines to understand and generate human language, facilitating advanced human-computer interaction and knowledge extraction. However, the complexity of human language presents significant obstacles, particularly in managing linguistic ambiguity, contextual nuances,
Natural Language Processing (NLP) is a pivotal subfield of artificial intelligence (AI) that focuses on the interaction between computers and human language. By enabling machines to understand, interpret, and generate human language, NLP bridges the gap between human communication and computational systems. This essay explores the fundamentals of NLP, its
