Housing dataset

Housing Dataset Analysis Project Overview This project focuses on analyzing the Housing Dataset to understand the factors that influence house prices. The notebook includes data preprocessing, exploratory analysis, and regression modeling to predict housing prices. Features - Data cleaning and preprocessing - Exploratory Data Analysis (EDA) - Visualizations of relationships between features and prices - Implementation of **Linear Regression model** - Evaluation of model performance using error metrics Technologies Used - Python - Pandas - NumPy - Matplotlib / Seaborn - Scikit-learn Results - Correlation heatmaps of housing features - Scatter plots of price vs key features - Regression model with metrics such as RMSE, MAE, R² - Insights into the most significant predictors of price