tatha04/Housing-Prices-Advanced-Regression-Techniques

This notebook explores the housing dataset from Kaggle to predict Sales Prices of housing using advanced regression techniques such as feature engineering and gradient boosting.

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Accurately predict the final sale price of homes using a dataset of various property characteristics. By analyzing factors like square footage, number of rooms, and location, it generates a precise estimated sale price. This tool is for real estate agents, appraisers, investors, or homeowners looking to understand property valuation.

No commits in the last 6 months.

Use this if you need to quickly and accurately estimate the market value of residential properties based on their features.

Not ideal if you're looking for a simple, on-the-fly calculator without providing detailed property attributes.

real-estate-valuation property-appraisal home-sales-prediction market-analysis housing-investment
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Language

Jupyter Notebook

License

MIT

Last pushed

Jun 03, 2021

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