I created the numpy-house-price-regression repository to build a complete end‑to‑end house‑price regressor using only NumPy. The pipeline cleans tabular features, engineers simple derived and categorical encodings, splits the data reproducibly, fits OLS via the normal equation, and reports MAE, RMSE, R‑squared plus residual statistics on a held‑out test set. The repo lives on my GitHub under the username my GitHub profile.
- Project title: numpy-house-price-regression
python scaffold.py
The checklist has 24 pipeline steps; currently only step 1 (impute_nan_with_mean) is marked complete.
- Goal: Build a complete end‑to‑end house‑price regressor in pure NumPy
- Language: Python
- Repository host: @Sudeepcpc’s GitHub
- Development timeline: Started 2026‑10, last updated 2026‑10
- Completed step: impute_nan_with_mean