Data Annotation (https://macgence.com/blog/a-brief-guide-about-the-data-annotation/) is the process of labeling or tagging data to provide meaningful information for machine learning algorithms. It involves adding annotations or meta data to raw data, making it understandable for computers. By doing this, AI and ML models can learn from the labeled data to recognize patterns and make predictions.
In these, various types of data can be label, such as images, text, videos, audio, and sensor data. This label can take the form of bounding boxes, semantic segmentation, image classification tags, named entity recognition, or sentiment analysis labels.