NBA Playoff and Player Statistics Prediction
- Developed a predictive machine learning model using Python and Pandas to analyze historical NBA data and forecast playoff outcomes and player statistics, employing K-means clustering to segment player performance.
- Enhanced model accuracy with regression analysis and machine learning algorithms, improving predictions for player contributions and team performance.
- Implemented data visualizations to communicate insights effectively, supporting strategic decisions in fantasy sports and betting, showcasing advanced data manipulation in sports analytics leading to our project getting recognized and funded for further research.
CTA (Chicago Traffic Association) Tracker
- Led the development of an open-source CTA Tracker to enhance Chicago public transit efficiency through detailed data analysis of ridership patterns and trends.
- Managed multiple project phases, from data collection and method formulation to analysis and presentation of findings, contributing significantly to project success leading to our 97% grade.
Fraud Detection for Velera
- Integrated and cleaned large volumes of transactional data in Snowflake, engineering features for effective fraud detection.Developed, trained, and deployed machine learning models in Python to Snowflake for real-time fraud detection.
- Created dashboards in Power BI/ to monitor fraud detection, providing stakeholders with actionable insights and updates