house prices dataset

House Prices Data Analysis Project

Analyzed real estate data to understand pricing trends and factors influencing property values. Key tasks included:

Cleaning and preprocessing dataset (handling missing values, encoding categorical variables, normalizing data).

Performing exploratory data analysis to identify key features affecting house prices.

Creating visualizations like scatter plots, histograms, and correlation heatmaps to present insights.

Developing predictive models (e.g., linear regression, decision trees) to estimate house prices.

Evaluating model performance using metrics like RMSE and R².

Tools: Python, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn