Skip to content

Latest commit

 

History

History
3 lines (2 loc) · 548 Bytes

File metadata and controls

3 lines (2 loc) · 548 Bytes

Article 2: Natural Language Processing Fundamentals

Natural language processing enables computers to understand, interpret, and generate human language. Key techniques include tokenization, part-of-speech tagging, named entity recognition, and sentiment analysis. Modern NLP leverages transformer architectures like BERT and GPT models for tasks such as language translation, text summarization, and question answering. Applications span chatbots, voice assistants, content moderation, and automated document analysis across various industries.