Train a regression model on a public housing dataset and evaluate it.
Difficulty: Intermediate · Technology: Python, scikit-learn
Features to build
- Data cleaning
- Feature selection
- Model comparison
- Error metrics explained
Step-by-step build plan
- Pick a public housing dataset
- Clean it and explore distributions
- Split into train and test sets
- Compare at least two models
- Explain errors in plain language
The part most people find hard
Avoiding leaking test data into training.
How to test it
Report error on the test set only.
Suggested extensions
Add user accounts, better error handling, automated tests and a README with screenshots. Each extension is a new talking point in interviews.
How to describe it on your resume
Built and evaluated regression models for house price prediction.
Portfolio tip
Deploy it, link both the live version and the code, and write two paragraphs about what you learned and what you would improve.