Data Labelling

Data labeling is the process of annotating and categorizing data samples to train machine learning models and algorithms. It involves tasks such as image tagging, text annotation, and object detection for generating labeled datasets that serve as input for supervised learning algorithms. Readers can explore data labeling techniques, tools, and best practices for collecting high-quality training data, ensuring model accuracy and generalization performance in machine learning applications.