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Clickworker
Data Annotation Tech
Encord
HiveMind
Playment
Snorkel AI
Supervisely
V7 Labs
Video
Document
Medical DicomFor the past two years, I have been deeply immersed in AI development, specializing in data annotation and labeling using the Atlas Capture platform. In this role, I have served as a critical link between raw data and machine learning models, ensuring they are built on a foundation of high-quality, accurately structured data. Working extensively within the Atlas Capture ecosystem, I have mastered a variety of complex annotation tasks, including image segmentation, entity tagging, and sentiment analysis. My daily workflow involves meticulous attention to detail, as I categorize vast datasets to help AI systems recognize patterns, understand natural language, and navigate visual environments with increasing precision. Beyond just "labeling," my experience has taught me to navigate strict project guidelines while maintaining high inter-annotator agreement scores. I understand that the performance of a model is only as good as the data it is fed; therefore, I prioritize consistency and accuracy to minimize bias and error. This two-year tenure has not only sharpened my technical proficiency with industry-standard labeling tools but has also given me a unique perspective on the iterative nature of supervised learning and the evolving needs of the AI landscape.
it refers to labeling tasks in which you merge videos while avoiding merging beyond 40s and thereafter saving the work and submiting your work
BACHELOR OF TECHNOLOGY, ICT
CYBER MANAGER
