Machine Learning

House Price Prediction

Developed prediction models using the Ames, IA house prices dataset, demonstrating the full Data Science lifecycle: Define, Discover, Develop and Deploy. Established a baseline OLS regression model, then developed Random Forest, XGBoost, and LightGBM models, comparing performance against the baseline.

Domain

Finance / Real Estate

Methods

  • OLS Regression
  • Random Forest
  • XGBoost
  • LightGBM

Tools

  • Python
  • scikit-learn
  • XGBoost
  • LightGBM

Impact / Outcome

Demonstrated end-to-end ML pipeline for price prediction applicable to housing agencies, banks, and real estate companies.

View on GitHub