Image Annotation
Worked on a project in which I had to evaluate regenerated images and their originals, and pick the closest match quality wise and in similarity.
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With hands-on experience in data annotation across text, audio and images, I bring a strong ability to produce accurate, high-quality training datasets for AI and machine learning models. I've worked extensively with large, diverse datasets and consistently deliver 97% accuracy in labelling, verification, and quality checks. My experience spans entity tagging, sentiment labelling, transcription, speaker identification, object detection, and contextual classification - giving me a well-rounded understanding of how precise data contributes to model performance. What sets me apart is my attention to detail, consistency, and ability to follow complex guidelines while still thinking critically. I've supported iterative model improvements by reviewing AI outputs and providing meaningful feedback to enhance accuracy. I'm comfortable with annotation tools, SOP-driven workflows, and documentation processes, and I stay updated on best practices in AI and ML. I approach data annotation with patience, curiosity, and a genuine commitment to producing reliable, human-aligned training data.
Worked on a project in which I had to evaluate regenerated images and their originals, and pick the closest match quality wise and in similarity.
Worked on a project in which I had to listen to Audio files and evaluate them according to pronunciation, tone, emotion detection, grammatical mistakes etc and rate them accordingly
I worked on a project in which I had to annotate images from Instagram profiles and had to label their contents as per the categories provided like person, landmark, clothing, accessories, animals etc.
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