Dataset annotation is a crucial process in machine learning and artificial intelligence, as it ensures that models learn from accurate and labeled data. It involves tagging data with relevant labels, allowing algorithms to interpret and make predictions based on the inputs. This labeling can be applied to images, text, audio, and other data types, making it essential for developing reliable and efficient models. The quality of annotations directly influences the performance of machine learning models, and as such, it plays an integral role in the success of AI projects. Methods of Dataset Annotation There are several methods for dataset annotation,…