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Developed an ensemble voting model that included Random Forests, Linear Regression, Orthogonal Matching Pursuit, and Gradient Boosting Regressor to predict future solar power generated by a solar plant in India at 98.7% accuracy. Placed 1st at the Virginia Tech Computational Modeling & Data Analytics Fall 2022 Data Competition.

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ensemble-learning data-science gradient-boosting-regressor linear-regression machine-learning-algorithms orthogonal-matching-persuit random-forest solar-power

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