Authors: Samarth D
Abstract: This project provides a comprehensive analysis and prediction of California housing prices using machine learning techniques. The project is implemented in Python and uses a Linear Regression model to predict housing prices based on various factors such as median income, housing median age, total rooms, population, and geographical location. The report is structured to provide an in-depth understanding of the problem, methodology, implementation, results, and potential future work. The accompanying Python code trains the model, evaluates its performance, and produces visualizations to aid in understanding the relationships between features and housing prices
