Computer vision and machine learning are both areas of artificial intelligence (AI), but they study different things and are used in different ways. Machine learning, or ML, is a more general area that studies how to make algorithms that computers can use to learn from data and make predictions. It can be used on different kinds of data, like numerical, textual, and visual data. It's used in systems that make suggestions, find scams, and plan maintenance ahead of time.
Computer vision, on the other hand, is a branch of machine learning that focuses on making it possible for computers to understand and process visual information from the world, like pictures and videos. To carry out tasks like object detection, image classification, and feature extraction, it uses methods like image processing, feature extraction, and facial recognition. Although computer vision usually needs a lot of labeled training data to achieve high accuracy, machine learning can work with both labeled and unlabeled data.