Developed a comprehensive machine learning

Developed a comprehensive machine learning solution to predict insurance charges using linear regression and advanced data science techniques. The project involved complete end-to-end implementation including exploratory data analysis (EDA), data cleaning, feature engineering, and model evaluation. Tech Stack: Python, NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn, Jupyter Notebook The model demonstrates strong statistical significance in predicting insurance charges across diverse demographic segments.