How To Contribute To Open Source Documentations





Documentations Are of Great Value, But they are neglected sometimes, In this Devsprint We Will Focus on how to Contribute to Documentation of Machine Learning Opensource Projects.

Look for and read the CONTRIBUTING file Open source projects have a CONTRIBUTING section or look out the issues taged with "Documentation"

Ideas Participate in an Issues thread or start your own to have your voice heard.

Write Fork the Repository then Contribute your expertise in an area by helping The organization expand the included content, Fix typos, clarify language, and generally improve the quality of the content. Fix issues or contribute new features. Help keep content easy to read with consistent formatting

Appropriate language and formatting are the basic design elements of documentation. A format that shows a hierarchical structure and a coordinate structure of information lead the fellow developer through the text. Using appropriate language is significant in providing the fellow developer with a thorough understanding of the purpose of the documentation.

Use language with precision Prefer simple direct expression of ideas.

Outline sections

Help The Organisation to ensure that this repository is comprehensive. if there is a topic that is overlooked, please add it, even if it is just a stub in the form of a header and single sentence. Initially, most things fall into this category.

Create a Pull Request Create a Pull Request after committing your work, If the Member of the organization accepts it they’ll merge in the changes into the repository. If not they may ask you to change the wording after having a discussion in the comments on the pull request. Or they may not merge the Pull request(which is completely fine as this experience will help you next time)

So one can contribute to projects without the need to even code


This is a Beginners Devsprint no Prerequisite is required but Knowledge Of Machine Learning will be Appriciated

Content URLs:

Speaker Info:

I am pursuing computer science engineering and my domain of work is Deep Learning and Machine Learning. I have Contributed to sciket learn and Matplotlib.

Speaker Links:

Id: 1660
Section: Data Science, Machine Learning and AI
Type: DevSprint
Target Audience: Beginner
Last Updated: