Project Description
Built supervised machine learning models that can predict the price of apartments in the city of Buenos Aires — with a focus on apartments that cost less than $400,000 USD.
Overview
- Created linear regression models using the scikit-learn library
- Built data pipelines for imputing missing values and encoding categorical features
- Improved models performance by reducing overfitting
- Created a dynamic dashboard for interacting with completed models
Language & Tools
- Python (Pandas, Matplotlib, Plotly, Scikit-learn)
View Source
- To view featured notebooks, please send me an email at donald@donaldghazi.com