Data Lake

Data labeling involves annotating raw data, such as images, text, or videos, with meaningful tags or categories. This process enables supervised machine learning models to learn patterns and make accurate predictions. Proper labeling is crucial for model accuracy, as it provides the necessary ground truth for training algorithms to understand and classify data effectively.