Airbnb Rating Prediction

Duration: June 2020 – Present

Skills Used

  • Python
  • Pandas
  • Scikit-learn
  • Random Forest
  • Linear Regression

Project Details

  • Built a predictive model for Airbnb review scores, improving accuracy by 3% through hyperparameter tuning.
  • Preprocessed data with imputation, scaling, and one-hot encoding, optimizing model performance.
  • Used Jupyter for analysis and visualization, achieving a MAE of 0.298 with the Random Forest model.

Key Achievements

  • 3% improvement in prediction accuracy
  • MAE of 0.298 with Random Forest model
  • Effective data preprocessing and model optimization