Data Labeling: The Authoritative Guide
Data labeling is one of the most critical activities in the machine learning lifecycle, though it is often overlooked in its importance. Powered by enormous amounts of data, machine learning algorithms are incredibly good at learning and detecting patterns in data and making useful predictions, all without being explicitly programmed to do so. Data labeling is necessary to make this data understandable to machine learning models.| scale.com
