The process of classifying unstructured data and information in order to train machine learning models is known as data annotation. We are surrounded by massive amounts of unprocessed data these days. Various formats, including text, audio, video, and photos, are available for this raw data.
Well-labeled and high-quality data aid supervised machine learning models in item identification, sentiment analysis, speech recognition, and even driving.
Computer vision models are trained to detect and identify items by labeling video material by experts. For usage in self-driving cars, drones, robotics, and other applications, offers a variety of video annotation services, such as bounding box annotation, polygon annotation, key point annotation, and semantic segmentation.
Natural language processing and machine learning models such as chatbots, offers text annotation services such as sentiment analysis, intent analysis, named-entity recognition, and entity classification. These services help the models comprehend text and metadata for purposes such as sentiment analysis, spam & intent detection, and more.
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