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bengaluru-house-price-prediction

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panubhav2001 / bengaluru-house-price

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Developed a Bengaluru house price prediction project using Python libraries like Pandas, NumPy, Matplotlib, Seaborn, and scikit-learn. Implemented data cleaning, feature engineering, and model evaluation with techniques such as median imputation, outlier removal, and Random Forest modeling (R-square: 0.72, MAPE: 0.18). Deployed the model via Flask

bootstrap flask machine-learning random-forest scikit-learn eda pandas feature-extraction feature-engineering ensemble-model pickling bengaluru-house-price-prediction
  • Updated Aug 3, 2024
  • Jupyter Notebook

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