Freelancer

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Freelancer Overview

My closest experience with AI training and data labeling comes from my hands-on machine learning work, where I built and trained a Titanic survival prediction model using Python. This involved the complete data preparation pipeline — handling missing values, cleaning raw datasets, feature engineering, and labeling target variables for supervised learning. I developed a strong understanding of how data quality directly impacts model performance, which is fundamentally what data labeling work is about. Beyond that project, my academic research background in agroforestry at FUNAAB required rigorous data collection, classification, and annotation of field observations — work that mirrors the precision and consistency required in professional data labeling. My cybersecurity projects, particularly my OWASP vulnerability lab, also involved categorizing and tagging threat patterns, which required the same structured, detail-oriented thinking that AI annotation demands.

Education

Work History