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https://github.com/ahmad-ali-rafique/usa-house_price-predict

A Streamlit application for predicting house prices in the USA using a linear regression model.
https://github.com/ahmad-ali-rafique/usa-house_price-predict

artificial-intelligence data-science deep-neural-networks house house-price-prediction linear-regression machine-learning modeling neural-networks price-prediction regression-models streamlit usa

Last synced: 4 days ago
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A Streamlit application for predicting house prices in the USA using a linear regression model.

Host: GitHub
URL: https://github.com/ahmad-ali-rafique/usa-house_price-predict
Owner: Ahmad-Ali-Rafique
Created: 2024-08-23T13:39:42.000Z (3 months ago)
Default Branch: main
Last Pushed: 2024-08-23T14:38:23.000Z (3 months ago)
Last Synced: 2024-10-11T09:22:30.331Z (27 days ago)
Topics: artificial-intelligence, data-science, deep-neural-networks, house, house-price-prediction, linear-regression, machine-learning, modeling, neural-networks, price-prediction, regression-models, streamlit, usa
Language: Python
Homepage:
Size: 12.9 MB
Stars: 0
Watchers: 2
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

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README

![Ahmad Ali Rafique](https://github.com/Ahmad-Ali-Rafique/USA-House_Price-Predict/blob/main/house%20price%20prediction.png)
## Ahmad Ali Rafique

I am an AI & Machine Learning Specialist with expertise in developing and deploying machine learning models for various applications. With a strong foundation in deep learning, natural language processing, and data science, I am dedicated to building innovative solutions that address real-world challenges.

### Project Overview

This repository contains a Streamlit-based application designed for predicting house prices in the USA using a linear regression model. The application provides an interactive interface where users can input details about a house, such as square footage, number of bedrooms, bathrooms, floors, and zip code, to receive an estimated price.

### Key Features

- **User Input:** The application allows users to enter information about the house's characteristics.
- **Prediction:** The model generates an estimated price based on the input features.
- **Model:** The predictions are based on a linear regression model trained with historical housing data.
- **User Interface:** Built using Streamlit, providing a simple and intuitive interface for users to interact with.

### Skills and Technologies Used

- **Streamlit:** For creating interactive web applications.
- **Scikit-learn:** For loading and using the linear regression model.
- **NumPy:** For handling numerical operations and preparing input data.
- **Joblib:** For loading the pre-trained model.

### About the Model

The linear regression model used in this project has been trained on historical data to predict house prices based on several features. The model is designed to provide users with an estimated price based on the input they provide, helping them understand potential market value.

### Contact

Feel free to connect with me for any questions or collaborations:
- **GitHub:** [Ahmad-Ali-Rafique](https://github.com/Ahmad-Ali-Rafique)
- **LinkedIn:** [Ahmad Ali Rafique](https://www.linkedin.com/in/ahmad-ali-rafique)

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Thank you for checking out my project! I am always looking for new challenges and opportunities to apply my skills and knowledge in machine learning and AI.