I will do machine learning projects

I develop machine learning solutions using Python, Scikit-learn, XGBoost, and supervised and reinforcement learning techniques, including classification, regression, feature engineering, model optimization, and evaluation.

I am entering the fifth and final year of my five-year Artificial Intelligence Engineering degree.

My tennis analytics project uses XGBoost to estimate point-winning probabilities from shot-by-shot match data, evaluated on over 700,000 shots from 970 matches. I also developed a Q-Learning simulation for dog separation anxiety, where an agent learns a behavioral policy through rewards, exploration, and repeated interactions. These projects demonstrate practical experience with predictive modeling and sequential decision-making.