Project House
House Price Prediction
#Machine LearningRandom Forest Algorithm
Table Of Content

Abstract

House price prediction is an essential topic of real estate. This project, the House Price Prediction system, uses a Random Forest Regression algorithm for house price prediction. The Python Flask framework is employed to create an API that serves as an intermediary between the model and the mobile application developed using React Native. The React Native mobile application consists of two modules: User and Contractor. Users can select house features for price prediction, publish posts for contractors, and evaluate contractor applications. Contractors, on the other hand, can view user posts and submit applications with finalized pricing.

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Technologies Used

FrontendReact Native
BackendFirebase, Python
AlgorithmRandom Forest
Accuracy75%
Project IDML002A

Modules

  1. Customer
  • 🏠 Login/Signup
  • 🏠 Predict House Price
  • 🏠Publish Contract Post
  • 🏠 View Applications from contractors
  • 🏠 Pick a contractor
  1. Contractor
  • 🏠 View Contract Posts
  • 🏠 Login/Signup
  • 🏠 Apply for contracts
  • 🏠 View Application status