Developed and implemented a machine learning project utilizing the K-Nearest Neighbors (KNN) algorithm to classify over 1000 different genre songs, achieving an impressive 83% accuracy rate in predicting audio genre. Conducted data preprocessing and analysis on a diverse dataset of audio recordings to extract relevant features for accurate genre classification.
Developed a traffic intersection simulator in C++ that accurately simulated the movement of vehicles at an intersection. The simulation incorporated traffic lights and enforced traffic laws to ensure the realistic flow of traffic. Implemented a user interface where the simulation could be controlled by pressing the "Enter" button, allowing cars from four sides to move one square at a time, mimicking a real-life intersection scenario.
Helped create a project designed to enhance the efficiency and effectiveness of Arm in Arm, a food distribution pantry. The project aimed to streamline client service, lessen wait times, better volunteer coordination, and improve overall management through an integrated system comprising appointment scheduling, pre-registration, and volunteer assignment.