house-rent-prediction

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Hamada-khairi / PFDA-Hamada

A comprehensive R-based data analysis project that examines housing rental patterns across multiple cities, utilizing statistical methods and visualization techniques to analyze 4,746 properties' data points including rent prices, locations, and amenities. The project employs various R libraries to clean, process, and visualize rental market trends

data-science ggplot2 data-analysis apu r-studio data-visualization-project data-analysis-in-r r-programming-projects data-cleaning-and-preprocessing data-processing-and-analysis real-estate-analytics r-statistics house-rent-prediction

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R

prathams0ni / Mumbai_House_Rent_Prediction_EDA_ML_Streamlit_Deployment

Star

A complete end-to-end machine learning project to predict monthly house rent in Mumbai using data cleaning, outlier handling, feature encoding, and regression models (Linear Regression, Decision Tree, Random Forest). The best model is deployed as a Streamlit web app for real-time rent prediction.

python data-science machine-learning random-forest numpy linear-regression scikit-learn regression eda pandas outlier-detection feature-engineering data-cleaning decision-tree mumbai model-deployment streamlit streamlit-app house-rent-prediction

Updated
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