I’m someone who enjoys learning fast and building things that actually work in real life. My skills span across machine learning, data science, and software development, and I’ve developed a strong interest in solving practical problems with technology. I’ve worked on interesting projects such as a fake-job detection system, a real estate price prediction model, and risk-based machine learning systems that combine probability, statistics, and data analysis. I like working on projects where data can reveal hidden patterns—whether it’s predicting credit risk, analyzing traffic accident probability, or detecting fraudulent behavior.
I’m comfortable working with Python, machine learning libraries, data preprocessing, and model building techniques like Random Forest and XGBoost. I also enjoy building dashboards, experimenting with LLM-based applications, and improving model performance through feature engineering. Overall, I’m driven by curiosity and the excitement of turning raw ideas into working, intelligent systems.