https://github.com/arya2004/xcelerate

end to end ML project with azure CI/CD
https://github.com/arya2004/xcelerate

Last synced: 5 days 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 (8 months ago)
• Default Branch: main
• Last Pushed: 2024-03-29T18:54:48.000Z (8 months ago)
• Last Synced: 2024-04-06T16:40:21.559Z (8 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 1.13 MB
• Stars: 0
• 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)