Final Year Project of building a Real Estate Website using MERN Stack.

A full-stack web application for browsing and managing real estate listings, built with React for the frontend and Node.js with MongoDB for the backend. Features property search, user authentication, and a responsive interface for seamless real estate exploration.

A demo showcase of a comprehensive MCP Server setup using a real estate websites and companies data. This MCP has been incorporated into several other related real estate (renting, buying, consulting) projects. Reach out to me personally if you work on similar projects or would like to just have a bainstorm session!

This is my practical project of python django complete website of Real Estate sharing with you guys.

A REAL ESTATE :house: :hotel: website built using only DJANGO as framework :star2: My First Django Fullstack Project :statue_of_liberty: . Contributions are encouraged and welcomed :heavy_check_mark:

This is a Real E-state Site Project Made with Laravel, Bootstarp, JQuery, DataTables, FacyApp. I only made it for my College Project, but if you are here that means I might have posted it online somewhere and you are here to steal it or see as refrence, but it's okay.

This is a Python project that uses BeautifulSoup and requests libraries to scrape real estate data from a website and store it in a database and a text file or a CSV file.

The project ‘Vihar Valley’ is a real estate related website made using HTML and CSS for clients to get to know about what the company is about and their services.

Welcome to GetFlats – your ultimate destination for seamless property exploration and investment opportunities. Revolutionizing the way you discover your next home or lucrative investment, GetFlats combines innovative technology with personalized service. With our intuitive interface and extensive database,finding your ideal property is effortless.

Database lab project. Created a real estate website on which you can add and sell properties using asp.net

This is my first project using Node.js. With this website my project is a real estate sale and purchase, with a client administrator.

This is a fully responsive real estate website designed using HTML, CSS, and JavaScript. It provides an intuitive, clean, and modern user interface for showcasing property listings, real estate services, and contact information. This project demonstrates front-end web development skills focused on layout design, user experience, and responsive mobi

This website was design for yearly exhibition carried out by Exquisite Residence Real Estate Company.The website showcased previous exhibitions and invited guest for upcoming exhibition. I used Html, CSS and JavaScript technology in executing this project.

Gathers prices of real estate projects published on authority website.

Real Estate Website Project!

First part of real estate prediction price project. - Scraping Immoweb website (with their consent)

This project is developed by raw PHP. It is simple and workable project.

Django real estate website project

A real estate website project for the course Internet Engineering

A semester project of senior year university - small website for real estate management

This project is a website dedicated to the real estate sector. Among its features, the ability to register and view ads stands out, with a login option. The website has an exclusive section for the details of each property. Each property has advertiser information (phone, email) and a contact form.

This is the 5th semester Project. It is Real Estate Project and based on Html, CSS and JS.

The main objective of this web portal is to have an interface between builders and buyers with the registration of projects and escrow accounts. All the details of the builders and layout plan,status of sanctions and permissions from various departments and finally the timeline to finish the project can be processed. This can be implemented in many ways using different tools. We have chosen laravel to develop the portal using interactive user interface. Usually the stakeholders (buyers/builders) are provided with login id’s. The department of (L & B) RERA ACT maintains separate URL for query management. Some parts of the portal are made public. When a stakeholder submits a query it will be forwarded to the immediate authority of that department, a query will be logged into the database. Once the query is submitted, the timer for that query starts. Once the time taken for the response exceeds the timer limit the query gets triggered to the head of the department and necessary actions are taken. Using the logs maintained the Department of(L & B) RERA act finds associative patterns on the received queries. So that we can identify the problems and resolved in an optimized manner. This portal reduces unnecessary drift among the buyers. It makes easy for the authorities to resolve and provide solutions to these queries. It provides User friendly interface. It proves to be Robust.

Mobclip is a pet project that crawls real estate data from a website

My final year project which targets crawling real estate data from different websites and build a visualization platform.

This is a test project using next.js and Gsap. I might use this to rebuild my old wordpress real estate website

A modern and visually appealing **Real Estate website** built using **Vite + React.js**, featuring smooth animations, responsive design, and a functional contact form. This project serves as a **template for real estate agencies**, showcasing high-quality UI and frontend logic without backend integration (except the contact form).

This Python project is a web scraper for real estate data in Switzerland from the website [homegate.ch](https://www.homegate.ch). The scraper gathers information about properties based on user-defined parameters such as type (buy or rent), city, price, and room count.

This data science project series walks through step by step process of how to build a real estate price prediction website. I will first build a model using sklearn and linear regression using bangaluru housing prices dataset from kaggle.com. Second step would be to write a python flask server that uses the saved model to serve http requests. Third component is the website built in html, css, bootstrap and javascript that allows user to enter home square ft area, bedrooms etc and it will call python flask server to retrieve the predicted price. During model building I will cover data science concepts such as data loading and cleaning, outlier detection and removal, feature engineering, dimensionality reduction, gridsearchcv for hyperparameter tunning, k fold cross validation etc.

This data science project series walks through step by step process of how to build a real estate price prediction website. We will first build a model using sklearn and linear regression using banglore home prices dataset from kaggle.com. Second step would be to write a python flask server that uses the saved model to serve http requests. Third component is the website built in html, css and javascript that allows user to enter home square ft area, bedrooms etc and it will call python flask server to retrieve the predicted price. During model building we will cover almost all data science concepts such as data load and cleaning, outlier detection and removal, feature engineering, dimensionality reduction, gridsearchcv for hyperparameter tunning, k fold cross validation etc. Technology and tools wise this project covers, 1. Python 2. Numpy and Pandas for data cleaning 3. Matplotlib for data visualization 4. Sklearn for model building 5. Jupyter notebook, visual studio code and pycharm as IDE