For the 2023 Chevron Rice Datathon, our team developed a model to predict 2020's renewable energy investments for each U.S. state, aiding Chevron in identifying potential collaboration opportunities. Our model focused on analyzing extensive datasets to forecast state-level renewable energy investment amounts, utilizing Linear, Lasso, and Ridge regression models to compare and optimize predictive accuracy as measured by the root mean squared error (RMSE), and implementing comprehensive data exploration and innovative modeling techniques to address the challenge of accurately predicting renewable investments.
Chevron Renewable Energy Investment Strategy
Built a predictive model for Chevron's 2023 Rice Datathon to forecast renewable energy investments by state. Used Linear, Lasso, and Ridge regression to optimize accuracy and identify collaboration opportunities.
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