COMP 7 Lecture Notes - Lecture 1: Labeled Data, Natural-Language Processing, Unsupervised Learning
Document Summary
Artificial intelligence (ai) refers to the ability of a computer or machine to perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. There are many different types of ai, including narrow or weak ai, which is designed to perform a specific task, and general or strong ai, which is designed to perform a wide range of tasks. Machine learning (ml) is a subfield of ai that involves training a computer or machine to learn and make decisions based on data, without being explicitly programmed. Ml algorithms are designed to improve their performance on a specific task over time by learning from data and experience. There are many different types of ml, including supervised learning, in which the machine is trained on labeled data, and unsupervised learning, in which the machine is not given any labeled data. Ai and ml are related, but they are not the same thing.
