San Gam

I’m a Computer Science student with a strong interest in Artificial Intelligence and Machine Learning. I focus on building and applying ML models to solve real-world problems using data-driven approaches, and I’m motivated to grow in the AI/ML field through hands-on experience and real applications.

Through practical project work, I’ve developed and tuned models end-to-end—from data preprocessing and feature engineering to training and evaluation. My Diabetes Prediction System reached 80–85% accuracy with Logistic Regression and Random Forest, while my QR Code Phishing Detection achieved 89–93% prediction accuracy through URL feature engineering and model tuning.

I also build predictive and recommendation solutions, including E-commerce Customer Behavior Prediction and an E-commerce Product Recommendation System using collaborative filtering and recommendation pipelines. I continue improving my skills by working with tools like Python, PyTorch, and MLOps/backend technologies such as Docker, MLflow, FastAPI, MariaDB, Redis, and Evidently AI.