What is a Data Labeling?

Detailed Deep Dive

Data labeling is the process of identifying raw data (such as images, text, or audio files) and adding informative tags or annotations to provide context for machine learning models. Labeling is the foundation of supervised learning, where models learn to recognize patterns based on these ground-truth labels. Because manual labeling is expensive and time-consuming, companies use automated data labeling tools, crowd-sourced annotation services, or self-supervised models to scale dataset creation.