My Projects
April 2024
Developer
Diabetes type-2 predictor
• Trained and compared Logistic Regression, CNN, and XGBoost models on a 100,000-sample diabetes dataset, achieving 95.4% accuracy with XGBoost. • Authored a 29-page research paper synthesizing 20+ studies and analyzing interpretability tradeoffs and feature importance.
June 2023
Developer
Sustainable Farming Predictor
• Built ML models (Decision Trees, K-Nearest Neighbors) to predict crop yields with R² scores exceeding 0.87, improving agricultural decision-making. • Analyzed 3,200 agricultural samples to uncover patterns promoting sustainability and generated actionable insights that increased prediction reliability by 22%.
December 2023
Developer
COVID-19 Learning Gap Analyzer
• Conducted statistical analysis on 5,000 student records, identifying a 12% increase in learning gaps among under-resourced schools. • Enhanced data visualization with Matplotlib and Seaborn, improving the clarity of key findings in final research reports by 30%.