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https://github.com/rayyan9477/house-price-prediction-model
This project aims to predict house prices using a machine learning model. The project involves data cleaning, feature engineering, model selection, training, and evaluation. The dataset is uploaded by the user, and the model is trained to predict house prices based on various features.
https://github.com/rayyan9477/house-price-prediction-model
data-science data-visualization gridsearchcv machine-learning machine-learning-algorithms notebook python random-forest
Last synced: about 1 month ago
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This project aims to predict house prices using a machine learning model. The project involves data cleaning, feature engineering, model selection, training, and evaluation. The dataset is uploaded by the user, and the model is trained to predict house prices based on various features.
- Host: GitHub
- URL: https://github.com/rayyan9477/house-price-prediction-model
- Owner: Rayyan9477
- License: apache-2.0
- Created: 2024-08-12T18:28:02.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-08-12T19:51:49.000Z (4 months ago)
- Last Synced: 2024-08-13T21:53:23.190Z (4 months ago)
- Topics: data-science, data-visualization, gridsearchcv, machine-learning, machine-learning-algorithms, notebook, python, random-forest
- Language: Jupyter Notebook
- Homepage:
- Size: 4.29 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
- License: LICENSE
Awesome Lists containing this project
README
# House Price Prediction Project
## Table of Contents
- [Introduction](#introduction)
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Dependencies](#dependencies)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)
## Introduction
This project aims to predict house prices using a machine learning model. The project involves data cleaning, feature engineering, model selection, training, and evaluation. The dataset is uploaded by the user, and the model is trained to predict house prices based on various features.
## Features
- Data Cleaning: Handling missing values for numerical and categorical data.
- Feature Engineering: Preprocessing numerical and categorical data.
- Model Selection: Using RandomForestRegressor for prediction.
- Model Training: Splitting data into training and testing sets.
- Model Evaluation: Calculating Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared (R2) score.
- Visualization: Plotting actual vs predicted house prices.
## Installation
Step-by-step instructions on how to install and set up your project.
1. Clone the repository:
```sh
git clone https://github.com/your-username/house-price-prediction.git
```
2. Navigate to the project directory:
```sh
cd house-price-prediction
```
3. Install the dependencies:
```sh
pip install -r requirements.txt
```
## Usage
Instructions on how to use your project. Provide examples and code snippets if necessary.
1. Run the Jupyter Notebook:
```sh
jupyter notebook app.ipynb
```
2. Upload the dataset when prompted.
3. The notebook will automatically process the data, train the model, and display the evaluation metrics and visualization.
## Dependencies
List all the dependencies required for your project. These should match the contents of your `requirements.txt` file.
- pandas
- numpy
- matplotlib
- seaborn
- scikit-learn
- google-colab
## Contributing
Guidelines for contributing to your project. Explain how others can contribute, report issues, or request features.
1. Fork the repository.
2. Create a new branch:
```sh
git checkout -b feature-branch
```
3. Make your changes and commit them:
```sh
git commit -m "Add new feature"
```
4. Push to the branch:
```sh
git push origin feature-branch
```
5. Open a pull request.
## Video Demonstration
Watch the video demonstration of the project:
Click the link to watch demo.
## Contact
Provide contact information for people who want to reach out to you. For example:
- Email: [email protected]
- GitHub: [Rayyan 9477](https://github.com/Rayyan9477)
- LinkedIn: [Rayyan Ahmed](https://www.linkedin.com/in/rayyan-ahmed9477/)