Labelled data is a dataset in which each data point is associated with a specific and well-defined label or category. These labels serve as annotations that provide context and meaning to the data, guiding machine learning algorithms to learn patterns and relationships accurately. The essence of labelled data lies in its critical role as the foundation for supervised learning, where algorithms are trained to predict or classify new, unlabeled data based on the patterns they’ve learned from the labelled examples.
Labelled data is an essential ingredient in training various machine learning models, including classifiers, regressors, and neural networks. It enables algorithms to understand the underlying structure of the data, distinguishing different classes or predicting continuous values. The process of annotating data requires human expertise to assign accurate labels, which can be time-consuming and costly. However, the quality of labelled data directly impacts the performance of AI models, making it a key factor in the success of supervised learning tasks.
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