Data Labeling

Data labeling identifies objects on raw data such as images, text, videos, and audio. The goal is to provide one or more informative labels to provide context so that a machine learning model can learn from it.

For example, labels might indicate whether a photo contains a train or a horse, which words were said in a voice recording, or if a lab image contains a tumor. Data labeling is required for various use cases, including computer vision, natural language processing, and speech recognition. Supervised machine learning models are built on large volumes of high-quality labeled data.