Language

Natural Language Processing in Everyday Applications Natural language processing, or NLP, helps computers understand and respond to human language. In everyday life, it powers tools we use every day: search boxes, chat apps, spell checkers, and voice helpers. With NLP, a phone can hear your words, a service can summarize a long article, and a message app can suggest the next emoji or phrase. The goal is to make technology easier and more natural to use. ...

Natural Language Processing: Machines That Understand Text Natural Language Processing, or NLP, helps computers interpret human language. It sits at the intersection of language and data science, turning text and speech into usable information. Tools range from simple spell checks to large models that can write sentences. The goal is to make software understand meaning, not just the words on the page. NLP works by moving text through several steps. First comes cleaning and tokenization, then grammar and meaning analysis. Modern systems rely on statistical methods and neural networks, not only fixed rules. The strongest models learn from vast text data and look at context across sentences and paragraphs, using representations called embeddings. ...

Natural Language Processing: Teaching Machines to Understand Language Natural Language Processing, or NLP, helps computers interpret human language. The aim is to turn text and speech into information we can act on. Most work starts with data from books, websites, and chats. A simple pipeline cleans text, splits it into tokens, and converts those tokens into numbers a computer can learn from. Recently, large neural networks called transformers have become common. They learn from huge text collections and can translate, summarize, or answer questions with decent fluency. ...