Data Augmentation

Data annotation involves tagging or labeling raw data—such as images, text, or audio—with meaningful tags, classifications, or metadata, enabling AI models to recognize patterns, make predictions, or understand content. This crucial step enhances model accuracy by providing high-quality, structured training data, and is fundamental to supervised learning processes in AI development.