Machine Learning Theory and Applications

4Natural Language Processing

Photo by Annamária Borsos

Natural language processing (NLP) refers to the branch of artificial intelligence (AI) focused on giving computers the ability to understand text and spoken words. It combines computational linguistics with statistical, machine learning, and deep learning models. The main idea is to process human language in the form of text or voice data. NLP has many applications such as understanding the intent and sentiment of a speaker or a writer, translating text from one language to another, responding to spoken commands, or summarizing large volumes of text. NLP can be found in voice‐operated global positioning systems (GPS), digital assistants, speech‐to‐text services, chatbots, named entity recognition, sentiment analysis, and text generation. Understanding human language is not an easy task, as a dialog contains many ambiguities such as sarcasms, metaphors, variations, and homonyms. When we say “understanding,” we need to be clear about the lack of consciousness of a machine. Alan Turing decided to dismiss these types of inquiries and ask a simple question: Can a computer talk like a human? To answer this question, he imagined the famous Turing Test in a paper published in 1950. A program called ELIZA subsequently succeeded in misleading people by mimicking a psychologist.

Python provides a wide range of tools and libraries ...