UNDERSTANDING NATURAL LANGUAGE PROCESSING (NLP) TECHNIQUES: FROM TEXT ANALYSIS TO LANGUAGE GENERATION

This technical article explores the evolution and current state of Natural Language Processing (NLP), focusing on its fundamental components, sentiment analysis capabilities, language generation techniques, and implementation considerations. The article examines the transformation of NLP through transformer-based architectures, discussing advancements in text preprocessing, tokenization methods, and named entity recognition. It analyzes the progression of sentiment analysis from basic lexicon-based approaches to sophisticated neural architectures, highlighting improvements in contextual understanding and emotional context detection. The article also investigates modern language generation systems, their architectural innovations, and practicalMohit Mittal https://iaeme.com/