Machine Learning
Airbnb Listing Price Modeling
A notebook-based tabular modeling project for predicting New York City Airbnb listing prices, covering task framing, train/test split, EDA, feature engineering, model training, and evaluation.
Period
May 2026
Tools / Tech
PythonPandasScikit-learnRandom ForestColumnTransformerGridSearchCV
Why I built it
I used this project to practice the full supervised learning workflow on a realistic tabular dataset with mixed numerical and categorical features.
Links
What it includes
- Frames listing price as a supervised regression problem.
- Uses preprocessing for mixed feature types and model comparison.
- Evaluates model behavior after feature engineering and hyperparameter search.
What I worked on
- Prepared train/test splits, exploratory analysis, and feature transformations in notebooks.
- Built a Scikit-learn workflow with ColumnTransformer and Random Forest modeling.
- Completed the notebook workflow myself as part of ML practice, including GridSearchCV tuning and result comparison.
What I Learned
- Strengthened practical understanding of feature preprocessing for tabular ML.
- Learned how model performance depends on task framing and data quality.
- Practiced interpreting regression results beyond a single score.