👉 A labeled fluid, often used in machine learning and data analysis, is a dataset where each data point is assigned a specific label or category. These labels represent the actual classifications or types of the data, such as "positive," "negative," "cat," "dog," or any other predefined categories. The primary purpose of labeled fluids is to train models and algorithms to recognize patterns and make accurate predictions or classifications based on new, unseen data. By providing these labeled examples, the model learns to map inputs to their corresponding outputs, enabling it to generalize and perform well on similar data in the future.
