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Code of Conduct

Our Commitment

At MLVerse-Math, we are committed to fostering an open, inclusive, collaborative, and respectful environment for everyone.

Our community exists to help learners, engineers, researchers, educators, and contributors collaborate in advancing Artificial Intelligence through open-source education, research, and innovation.

We believe that diverse perspectives strengthen our community and lead to better learning experiences, better research, and better software.


Our Values

We encourage all community members to:

  • Be respectful and professional.
  • Welcome newcomers and support learners.
  • Share knowledge openly.
  • Provide constructive feedback.
  • Respect different viewpoints and experiences.
  • Focus on collaboration and continuous learning.
  • Contribute positively to discussions and projects.

Expected Behavior

Examples of behavior that contribute to a positive environment include:

  • Using welcoming and inclusive language.
  • Being respectful of differing opinions and experiences.
  • Accepting constructive criticism gracefully.
  • Helping others learn and grow.
  • Giving credit where it is due.
  • Demonstrating empathy toward other community members.
  • Maintaining professionalism in discussions and contributions.

Unacceptable Behavior

The following behaviors are not tolerated within the MLVerse-Math community:

  • Harassment of any kind.
  • Personal attacks or insults.
  • Discriminatory or hateful language.
  • Threats or intimidation.
  • Trolling or deliberately disruptive behavior.
  • Publishing private information without consent.
  • Spamming, self-promotion, or malicious activities.
  • Plagiarism or misrepresentation of work.
  • Any conduct that would reasonably be considered inappropriate in a professional environment.

Community Standards

All contributors are expected to:

  • Follow repository guidelines.
  • Respect project maintainers and contributors.
  • Maintain a constructive and collaborative attitude.
  • Submit original work or properly attribute sources.
  • Follow open-source best practices.

When reviewing contributions:

  • Focus on the quality of the contribution.
  • Provide clear and actionable feedback.
  • Be respectful and professional at all times.

Open Source Collaboration

MLVerse-Math is built on the principles of:

  • Learning
  • Sharing
  • Research
  • Innovation
  • Open Collaboration

We encourage healthy discussions, thoughtful debates, and collaborative problem-solving.

Disagreements are natural, but they should always be handled respectfully and professionally.


Reporting Issues

If you experience or witness behavior that violates this Code of Conduct, please report it to the project maintainers.

When reporting an issue, include:

  • Description of the incident
  • Relevant links or screenshots
  • Date and time of occurrence
  • Any additional context

All reports will be reviewed fairly and confidentially.


Enforcement

Project maintainers are responsible for clarifying and enforcing community standards.

Actions for violations may include:

  1. Warning
  2. Temporary restriction from participation
  3. Removal of content
  4. Permanent removal from the community

Enforcement decisions will be made based on the severity and context of the violation.


Scope

This Code of Conduct applies to all MLVerse-Math community spaces, including:

  • GitHub repositories
  • Discussions
  • Issues
  • Pull Requests
  • Documentation
  • Community forums
  • Social and collaborative platforms associated with MLVerse-Math

Our Mission

MLVerse-Math aims to build one of the world's most comprehensive open-source ecosystems for:

  • Mathematics for AI
  • Machine Learning
  • Deep Learning
  • Generative AI
  • Large Language Models
  • AI Agents
  • MLOps
  • AI Research

Every contributor plays an important role in achieving this mission.


A Shared Responsibility

By participating in MLVerse-Math, you agree to uphold this Code of Conduct and contribute to a respectful, inclusive, and collaborative community.

Together, we can create an environment where people from all backgrounds can learn, build, research, and innovate.


Learn • Build • Research • Deploy

Building the Future of Open-Source AI Education