Welcome to the workshop!
Workshop
In ProgressWelcome to Crafting inclusive ML documentation and communication!
Today's icebreaker:
Inclusive or exclusive?
Start with a quick reflection on what makes documentation work or fail in diverse machine learning (ML) teams.
What’s one thing that makes ML documentation clear and inclusive — or confusing and exclusive?
Type your ideas in the chat.
Today's agenda:
- Review: Recap key concepts.
- **Practical exercise:**The InclusiveDocs challenge.
- **Closing:**Wrap-up and reflection.
Today's learning objectives:
- Translate ML results into clear, audience-focused documentation.
- Create reports that balance technical and business perspectives.
- Refine documentation for clarity, completeness and inclusion.
- Apply inclusive practices that build transparency and trust.
- Identify actions to improve communication in ML projects.