BLASTING-VOLUME-PREDICTION-A-DATA-DRIVEN-APPROACH-FOR-IMPROVED-ACCURACY

The dataset is of FY’23 and taken from iron ore mine of India.Aimed to predict volume of material blasted and visualise various blasting parameters to draw meaningful insights for decision-making in Steel Manufacturing sector. The project is enriched with concepts like exploratory data analysis(EDA),data cleaning,data visualisation,data transformation and machine learning algorithms.Supervised Machine Learning algorthims were applied and got best performance metric values as 0.976(r2-score) and 836.87(RMSE) for Linear Regression and DecisionTreeRegressor.