I developed a machine learning regression model alongside three other Berkeley Data Science Society members to predict NBA players’ average points per game (PPG) scored. We deployed hyperparameter tuning and cross validation techniques.

This project involved a deeper dive into machine learning model creation and optimization than any of my previous work. To see the Jupyter notebook for this project, click here.

Skills & tools: Python, feature engineering, hyperparameter tuning