Multi-Category Data Annotation for AI Model Training (Text & Image)
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Bounding BoxCompleted hands-on data annotation projects involving both text and image datasets to support machine learning model training. For text data, labeled over 3,000 samples including social media posts and product reviews for sentiment (positive, neutral, negative) and intent classification. Applied consistent annotation guidelines and handled ambiguous cases carefully to maintain labeling quality. For image data, annotated over 1,500 images using bounding boxes and classification tags across categories such as fashion items and everyday objects. Focused on accuracy, proper object boundaries, and consistency across datasets. Used annotation tools such as CVAT and basic spreadsheet workflows for structured labeling tasks. Maintained high attention to detail and performed self-quality checks to ensure reliable outputs.