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A Web App to predict rent of house.
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Apna Broker is Machine Learning based House Rent Predictor.

You can find the working Model by clicking here


This is Front-End of Apna-Broker Web Application. It has been created using AngularJS Framework.

We trained the model by Gradient Boosting Algorithm using XGBoost Library.

REST API was created using Flask.

Back-End of Web Application is hosted through HEROKU.

Technology Stack

  • HTML5 - Markup Language for Creating Web page.
  • CSS3 - Styling the Web Page for Interactive User Interface
  • Bootstrap 4 - Front-End Component Library for responsive and interactive web page
  • AngularJS - JavaScript-based open-source front-end web application framework
  • Flask - A microframework for Python
  • Gunicorn - A Python WSGI HTTP Server for Production/Deployment use.
  • Pickle - Used to save trained models/object
  • Numpy - Multidimensioanl Mathematical Computing
  • Pandas - Data manipulation and analysis for Python

Local Installation

  • Clone the repository
$ git clone
  • Then cd into cloned folder
$ cd /path/Apna-Broker
  • Open any of the local server for running application in browser like browsers-sync, lite-server, Simple HTTP Server
$ python3 -m http.server
  • Open your favorite browser and put in any of the following addresses and run the application:


This Web Application is still under alpha version, all developers are welcomed for contributions. Click here for more contributions guidelines.


The repository is licensed under MIT License Copyright (c) 2018 EvilCoders


The project is maintained by-

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