LINK: Github link

Project Objective

Build a baseline predictive model to estimate house prices based on property characteristics and evaluate the model’s explanatory power.

Dataset Overview

• Source: Kaggle (Boston housing dataset)
• Observations: Residential properties
• Target variable: House price (USD)

Key features

• Number of bathrooms
• Number of bedrooms
• House size (sqft)
• Lot size (sqft)
• Zip code

Model Specification

• Model: Multiple Linear Regression
• Training/Test split: 80% / 20%
• Evaluation metric: R² score

Key Results

• Test R²: 0.73
• The model explains approximately 73% of the variance in house prices.