Machine Learning Project to Predict House Prices in Bangalore.

Smart property valuation system using XGBoost machine learning for accurate house price predictions based on 13 real estate features

UrbanSphere is a powerful tool designed to assist potential buyers and residents by evaluating and ranking sub-districts of cities. It uses diverse parameters such as air quality, water quality, crime rate, and proximity to essential facilities to highlight the best areas for your needs.

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

Collection of interactive Tableau dashboards showcasing data visualization expertise across entertainment, real estate, and aviation industries. Features Netflix content analysis, housing market trends, and British Airways customer satisfaction metrics with advanced filtering and drill-down capabilities.

livabl real-estate data scraper

A simple tool for investors to find cash-flowing properties in Canada. Scans target cities, underwrites with a conservative cash-flow model, and ranks deals by margin of safety.

A multiple linear regression project to predict house prices using numerical property and neighborhood features, with model evaluation using R², MAE, and RMSE.

real estate python pipeline with clean data automation

Automated Commercial Property Analytics Pipeline: Python ETL, SQL Modelling, and Power BI Dashboard

This project predicts house prices in Bengaluru using multiple regression techniques. The goal is to build a machine learning model that takes in various features like location, size, number of bedrooms, and area, and outputs an estimated price of the property. 🔧 Models

Enterprise-grade real estate price intelligence platform implementing an end-to-end ML pipeline with advanced feature engineering, Gradient Boosting ensembles, cross-validated model evaluation, hyperparameter optimization, serialized model artifacts, automated inference, and Kaggle-grade batch prediction for production-ready valuation analytics.

Data Pre Processing in Python using a House Rent Project. Run in Jupyter Notebook. In this Project I do Data Preprocessing in that I clean Data & shows it in relevant manner

Institutional-grade liquidity and capital efficiency model for Dubai real estate using DLD transaction data. Detects rotation phases, exit velocity shifts, and structural risk clusters to support data-driven capital allocation decisions via advanced Power BI analytics.

UK energy certificate crawler

End-to-end data science project on King County house sales. Covers data cleaning, EDA, visualization, feature engineering, and regression modeling to predict housing prices. Showcases core skills in Python, ML, and insight communication

Zillow price history data

Multimodal property valuation system combining satellite imagery and structured housing data. Uses CNN-based visual embeddings + tabular features to predict real estate prices, with Grad-CAM explainability for spatial insights.

Data-driven analysis of the Ames Housing Dataset, combining advanced feature engineering and Stochastic Gradient Descent (SGD) regression model tuning. This repository showcases predictive modeling, hyperparameter optimization, and actionable insights for real estate analytics.

House Price Prediction is a machine learning project that analyzes real estate data to predict house prices based on various features like location, size, and amenities. It involves data preprocessing, exploratory data analysis (EDA), feature engineering, and model training using regression algorithms to provide accurate price estimates. 🚀📊🏡

A dual-mode Real Estate Intelligence Dashboard for Zimbabwe's top developers. Features automated Board Reporting (PDF), Leasing Feasibility Simulations, and Revenue Risk Detection using Python & Streamlit.

student housing listings intelligence

UK property listings and agent data extractor

Interactive Tableau dashboard analyzing King County real estate trends. Visualizes daily average sales prices, property condition heatmaps, and distribution metrics for bedrooms and bathrooms.

AirbnbNewYorkCityAnalysis is a comprehensive data analysis and visualization project exploring short-term Airbnb rental trends across New York City (2008–2022). Using open source Airbnb data, the project combines data cleaning, statistical summaries, and Tableau dashboards to uncover pricing patterns, borough level distribution, and insights.

Download unlimited Zillow listings for free, with no watermark and no registration required using our easy-to-use tool.

real estate property data extractor

Comprehensive Exploratory Data Analysis on Housing Market Pricing: uncover Feature Relationships, Pricing Patterns, and Key Value Drivers using Python and Data Visualization

Advanced portfolio analytics dashboard built with Next.js & TypeScript. Real-time asset valuation, multi-property comparison, investment horizon tracking, and sophisticated financial metrics. Investment analysis tool.

An AI-powered regression model designed to predict real estate prices. It features automated feature engineering, data preprocessing, and utilizes Machine Learning algorithms to provide accurate property valuations