https://github.com/21aja/house_price_prediction_revised_project
House price prediction using ML with Decision Tree Regressor achieving 100% accuracy. Preprocessing, EDA, and model evaluation applied using Python, Pandas, NumPy, Scikit-learn, and XGBoost for data-driven insights.
https://github.com/21aja/house_price_prediction_revised_project
decision-tree-classifier linear-regression numpy pandas xgboost
Last synced: 3 months ago
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House price prediction using ML with Decision Tree Regressor achieving 100% accuracy. Preprocessing, EDA, and model evaluation applied using Python, Pandas, NumPy, Scikit-learn, and XGBoost for data-driven insights.
- Host: GitHub
- URL: https://github.com/21aja/house_price_prediction_revised_project
- Owner: 21AJA
- License: gpl-3.0
- Created: 2025-03-24T08:43:10.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-24T09:01:55.000Z (over 1 year ago)
- Last Synced: 2025-04-04T03:17:54.983Z (over 1 year ago)
- Topics: decision-tree-classifier, linear-regression, numpy, pandas, xgboost
- Language: Jupyter Notebook
- Homepage: https://colab.research.google.com/drive/1KYUgDzEMxQLVZYzFw4De7dVrDb2yWTKU#scrollTo=ApkFy0EPgYlX
- Size: 865 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0