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LabelboxMercorNo subject matter listed
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TextI am a Computer Science student with strong experience in data-driven projects and a solid foundation in programming, data structures, and algorithms. I have hands-on experience working with Python, Pandas, NumPy, and Scikit-learn, particularly in building and optimizing machine learning models for real-world tasks such as air quality index prediction. My work involved data preprocessing, cleaning, feature engineering, and model evaluation using metrics like RMSE and R2 score, which has given me a keen eye for detail and accuracy—essential skills for data labeling and annotation roles. I am a quick learner, dedicated team player, and always eager to contribute to high-quality AI training data projects in domains like environmental data and health management systems.
Code Human Preference w/ Feedback focuses on capturing user preferences and continuously improving experiences through real-time feedback, ensuring systems adapt intelligently to human needs.
Code Human v2 is an evolved platform focused on building technology that feels intuitive, ethical, and human-centered. The project blends modern software engineering with thoughtful design to create systems that adapt to real human needs rather than forcing users to adapt to technology. Version 2 expands on the original concept with improved performance, smarter logic, and a stronger emphasis on usability, accessibility, and scalability. Code Human v2 aims to bridge the gap between code and human experience—making digital interactions more natural, meaningful, and efficient.
Bachelor of Technology, Computer Science
Higher Secondary Certificate, Science
Software Engineer
