Natural language processing (NLP)

NLP combines computational linguistics with statistical, machine learning, and deep learning models to process human language. It involves various tasks, including: text and speech processing (tokenization, stemming, part-of-speech tagging), syntactic analysis (parsing), semantic analysis (word sense disambiguation, named entity recognition), and pragmatic analysis (understanding context and intent). NLP powers applications like machine translation, chatbots, sentiment analysis, text summarization, and information retrieval. Recent advances in deep learning, particularly transformer networks, have significantly improved the performance of NLP systems, enabling more sophisticated and nuanced language understanding and generation capabilities. The field continues to evolve, addressing challenges such as understanding sarcasm, handling ambiguity, and adapting to different dialects and languages.