https://github.com/arya2004/xcelerate
end to end ML project with azure CI/CD
https://github.com/arya2004/xcelerate
Last synced: 11 months ago
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end to end ML project with azure CI/CD
- Host: GitHub
- URL: https://github.com/arya2004/xcelerate
- Owner: arya2004
- Created: 2024-03-28T17:14:32.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2025-01-26T14:58:43.000Z (over 1 year ago)
- Last Synced: 2025-03-01T20:17:19.506Z (over 1 year ago)
- Language: Python
- Homepage:
- Size: 1.13 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
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README
# Xcelerate
Xcelerate is an end-to-end machine learning project that predicts student exam performance using a Decision Tree model. It achieves a Best R-squared of 0.9994590956793753 with Decision Tree Regressor.
## Links
- Docker Hub: [Xcelerate Docker Image](https://hub.docker.com/repository/docker/zieglernattacatalyst/xcelerate/general)
- GitHub Repository: [Xcelerate GitHub](https://github.com/arya2004/xcelerate)
## Getting Started
### Docker Build
To build the Docker image for Xcelerate, run the following command in your terminal:
```bash
docker build -t xcelerate .
```
### Docker Run with Port Mapping
To run the Xcelerate app using Docker with port mapping to port 5000, use the following command:
```bash
docker run -p 5000:5000 xcelerate
```
The application will then be accessible at `http://localhost:5000`.
## Usage
1. Access the Xcelerate app through your browser at `http://localhost:5000`.
2. Follow the instructions on the web interface to input student data and predict exam performance.
3. View the prediction results on the web interface.
## Contributors
- [arya2004](https://github.com/arya2004)