| --- |
| title: House Price Prediction |
| emoji: 🏠 |
| colorFrom: blue |
| colorTo: green |
| sdk: gradio |
| sdk_version: 5.0.0 |
| app_file: app.py |
| python_version: 3.11 |
| pinned: false |
| --- |
| |
| # House Price Prediction |
|
|
| End-to-end machine learning app for predicting house sale prices with the Kaggle |
| `house-prices-advanced-regression-techniques` dataset. |
|
|
| ## Train |
|
|
| Set up Kaggle credentials, then download the dataset: |
|
|
| ```bash |
| python scripts/download_kaggle_data.py |
| ``` |
|
|
| Train the model: |
|
|
| ```bash |
| python -m src.train |
| ``` |
|
|
| If `data/raw/train.csv` is not present, training falls back to the included sample |
| dataset so the app remains runnable. |
|
|
| ## FastAPI |
|
|
| ```bash |
| uvicorn src.api:app --reload |
| ``` |
|
|
| Prediction endpoint: |
|
|
| ```http |
| POST /predict |
| ``` |
|
|
| ## Gradio |
|
|
| ```bash |
| python app.py |
| ``` |
|
|
| ## Hugging Face Spaces |
|
|
| This repository is configured for a Gradio Space. The target Space is: |
|
|
| ```text |
| pcsekhar/MLModels |
| ``` |
|
|
| Deploy with: |
|
|
| ```bash |
| hf upload --repo-type space --exclude "data/raw/*" --exclude ".git/*" --commit-message "Deploy house price predictor" pcsekhar/MLModels . |
| ``` |
|
|
