Apartment Price Prediction Using Machine Learning

Developed a Machine Learning regression model to predict apartment prices based on different property characteristics.

The project involved analyzing the dataset, handling missing values and data quality issues, preparing numerical and categorical features, selecting relevant features, training a regression model, and evaluating its performance using appropriate regression metrics.

The model uses property features such as area, number of rooms, bathrooms, floor level, year built, seller type, view, and other characteristics to estimate apartment prices.

**Tools:** Python, Pandas, NumPy, Matplotlib, Scikit-learn, Jupyter Notebook.