Data Analyst Intern
- Created a machine learning model that predicts the compressive strength of Fly Ash-based Geopolymer Concrete (FAGP)
- Operated Matplotlib, Seaborn & NumPy python libraries for data visualizations, mathematical calculations & array operations
- Performed Linear Regression, Random Forest Regression and XGBoost Regression machine learning models on dataset
- Obtained a R-squared score of 0.92 after performing the optimized hyperparameters with the XGBoost regression model
- Executed cross-validation to estimate the performance of XGBoost model with optimized hyperparameters on several subsets