https://github.com/anil951/shelter-guide

https://github.com/anil951/shelter-guide

css flask houseprice-prediction html js machinelearning maps ml python regression

Last synced: 7 days ago
JSON representation

• Host: GitHub
• URL: https://github.com/anil951/shelter-guide
• Owner: Anil951
• License: mit
• Created: 2023-05-28T10:31:39.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-08-05T15:49:35.000Z (over 1 year ago)
• Last Synced: 2024-11-07T09:40:59.350Z (about 2 months ago)
• Topics: css, flask, houseprice-prediction, html, js, machinelearning, maps, ml, python, regression
• Language: Jupyter Notebook
• Homepage: https://shelterguide.onrender.com/
• Size: 81.7 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Shelter Guide 

Welcome to Shelter Guide, the ultimate companion for all your housing needs! Shelter Guide is a powerful platform made using Machine-Learning,Python-Flask to assist users in predicting house prices and rent prices based on various factors. Our platform focuses on six metropolitan cities - Hyderabad,Bangalore,Delhi,Mumbai,Delhi,Kolkata, providing accurate  information to simplify your search for the perfect home.

## Features 

1. Price Prediction: Utilize our advanced algorithms to predict house and rent prices based on factors such as BHK, square footage, and nearby resources.

2. Interactive Map: Visualize available housing options and their corresponding locations within your preferred price range, making it easier to identify suitable neighborhoods.

3. Essential Factors: Consider essential amenities and nearby resources when making housing decisions, ensuring a comfortable and convenient living experience.Essenial amenities include Gas connection,parking,Security,Lift availability,Car parking and Nearby resources include Gym,School,Hospital,Play area and 8 more...

## Installation

1. Clone the repository from GitHub.

2. Install the required libraries using `pip install -r requirements.txt`.

3. Run the application using `python app.py`.

## Contributing

We welcome contributions from the community to enhance the system's capabilities and accuracy. Feel free to submit pull requests and report issues on GitHub.