Analyzed Spotify listening history to uncover behavioral patterns, usage trends, and artist preferences over time, using temporal and contextual features from user playback data.

Identified listening streaks, time-of-day preferences, platform usage trends, and repeat artist behavior across 5,000+ tracks from personal Spotify history.

Built a binary classification model to predict student depression from behavioral data using supervised learning.

Achieved high AUC score while handling a dataset of over 27,000 samples

Built a computer vision tool to detect and analyze coins in high-resolution images using OpenCV.

Successfully identified and measured circular objects with high visual clarity and precision

Built a Lebron-themed chatbot using NLP and custom regex patterns.

Achieved 85% chatbot intent accuracy

Explored box office trends for Marvel films using visualizations and analysis.

Visualized performance across 23 MCU films using 3 revenue metrics

Analyzed and visualized Superstore sales data using SQL and Power BI.

Identified top-performing product segments and trends across regions

Explored factors influencing student performance through dashboards.

Built an interactive dashboard analyzing habits across 3 student demographics