Implemented the project by using python, numpy, pandas, sklearn, xgboost and matplotlib. Conducted EDA on a data of 2 million rows performing feature engineering and categorical variable encoding. Compared R2 and RMSE scores of Multilinear regression, Decision tree, Random forest and XGBoost. Tuned the XGBoost model on selected parameters to achieve a R2 score of 76% and RMSE score of 18.1.
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