This repository focuses on research-oriented machine learning implementations. We welcome contributions that:
- Implement novel machine learning algorithms
- Improve existing implementations
- Add theoretical explanations or mathematical derivations
- Enhance documentation and testing
- Fix bugs or optimize performance
- Fork the repository
- Create a feature branch:
git checkout -b feature/your-feature-name
- Implement your changes following our coding standards
- Add tests for new functionality
- Update documentation as needed
- Submit a pull request
- Clear, documented mathematical foundations
- Efficient implementations with appropriate use of vectorization
- Comprehensive docstrings and inline comments
- Unit tests for all new functionality
- Type hints for Python functions
- PEP 8 compliance
- Mathematical derivations where applicable
- Complexity analysis
- Usage examples
- References to relevant papers or resources
- Ensure all tests pass
- Update relevant documentation
- Add entry to CHANGELOG.md
- Request review from maintainers
# Create virtual environment
python -m venv venv
source venv/bin/activate # or `venv\Scripts\activate` on Windows
# Install dependencies
pip install -r requirements.txt
# Run tests
python -m pytest
Open an issue for:
- Algorithm implementation discussions
- Theoretical questions
- Feature proposals
- Bug reports
- Focus on technical merit and scientific accuracy
- Provide constructive feedback
- Maintain professional communication
- Respect intellectual property and cite sources appropriately