Real Estate Prediction Model

Overview

This project focuses on developing a machine learning model for predicting house prices based on a set of features. The model is designed to assist a real estate company in making accurate price predictions, providing valuable insights for property buyers and sellers.

Features

• House Price Prediction: Predicts the price of houses based on various input features.
• Machine Learning: Utilizes machine learning techniques to improve prediction accuracy.
• Data Analysis: In-depth analysis of real estate data to identify key factors influencing house prices.

Technologies Used

• Programming Language: Python
• Machine Learning Libraries: scikit-learn, pandas, NumPy

Getting Started

1. Clone the Repository:

   git clone https://github.com/Deepak-Meena-github/Real-Estate-ML-Project/edit/main/README.md
   cd Real-Estate-ML-Project
   

• Install Dependencies: pip install -r requirements.txt -Run the application python app.py -train the model python train_model.py -Run the Application python app.py NOTE:Contributions are welcome! For major changes, please open an issue first to discuss what you would like to change.