Skip to content

Latest commit

 

History

History
50 lines (26 loc) · 2.65 KB

File metadata and controls

50 lines (26 loc) · 2.65 KB

Summer of Open Source ✨

We Welcome all, to GDSC's event, Summer of Open Source, an open source project allowing you to get familiar with the workings of open source and contribution mechanism, especially for GSOC and other open source events.

Levels of Difficulty

Basic: Basic projects that help introduce you to the world of Machine Learning, allowing contributors to get their hands dirty.

Intermediate: Intermediate projects for novices looking to apply what they have learned.

Advanced: Advanced projects for masters to showcase their abilities.

Getting Started 🚀

To contribute to ML-Projects, follow these steps:

  1. Fork the repository: Click the "Fork" button on the top right corner of this repository to create your own copy.

  2. Clone your fork: Clone the repository to your local machine using git clone https://github.com/your-username/ML-Projects.git.

  3. Create a new branch: Create a new branch for your changes using git checkout -b contributor-name/issue-name.

  4. Make your changes: Make your desired changes to the codebase. You can explore the datasets, improve existing models, develop new algorithms, update documentation, or fix bugs.

  5. Commit your changes: Once you've made your changes, stage them using git add . and commit them using git commit -m "Your commit message here".

  6. Push your changes: Push your changes to your forked repository using git push origin contributor-name/issue-name.

  7. Submit a Pull Request (PR): Go to your forked repository on GitHub and click the "New pull request" button. Provide a brief description of your changes and submit the PR for review.

Assigning Issues 📝

If you would like to work on a specific issue, comment on the issue or convey in the meetups expressing your interest in contributing. The project maintainers will review your request and may assign the issue to you if they believe you are a suitable candidate for the task.

Code Style Guidelines 📋

  • Use meaningful variable names and comments to improve code readability.
  • Ensure your code is well-documented and includes docstrings where necessary.

Code Review 👀

All contributions are subject to code review. A mentor/maintainer will review your PR, provide feedback, and merge it once it meets the project's standards.

Help and Support 🤝

If you need any help or have questions about contributing, feel free to reach out to us through GitHub issues.


Thank you for contributing to GDSC's event Summer of Open Source! Together, We aim to provide you with a platform to become familiar with machine learning and deep learning through open source. 🌟👩‍⚕️👨‍💻