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AppenNo subject matter listed
Video
ImageI am an experienced data annotator and quality analyst with a strong background in supporting AI training data pipelines across text, audio, and visual domains. My hands-on experience includes annotating over 500 visual contents, labeling objects, movements, scenes, and time-based events for computer vision projects, and evaluating search engine results to improve algorithms and recommendation systems. I excel at following complex guidelines, applying consistent judgment, and providing constructive feedback to ensure high-quality data. With a solid foundation in Computer Science and a Microsoft Certified: Azure AI Fundamentals certification, I am proficient with tools such as CVAT, Adobe Creative Suite, Microsoft Office, and Google Workspace. My attention to detail, contextual analysis, and fluency in English enable me to deliver accurate labeling, verification, and documentation for large-scale AI projects.
The project involves labelling video datasets in episodes. The videos are labelled in segments with a set of guidelines to be adhered to.
Performed data annotation and evaluation tasks on the Appen CrowdGen platform to support Artificial Intelligence and Machine Learning model development.
Bachelor of Science, Computer Science
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