ML Visuals
A shared collection of reusable science figures and slide templates for machine learning writing.
- Stars
- 17.4k
- Forks
- 1.5k
- Licence
- MIT
- Language
- —
- Last update
- 3.7 years ago
- Type
- Other
No commits in over a year — check for forks or alternatives before adopting.
What it is
ML Visuals is a community-made set of over 100 figures and templates, kept as Google Slides, that people can copy, edit, and reuse in machine learning presentations, blog posts, and papers. Its goal is to make technical diagrams clearer and more professional. Contributors add figures, and anyone can download them in common formats.
- Copy an existing figure slide into your own deck and adapt the labels
- Download a figure from the slides as an image for a blog post or paper
- Request a new figure by opening an issue on the GitHub repository
- Contribute your own diagram by adding a slide with author notes
Great for
- Machine learning students preparing presentations or thesis figures
- Researchers who want clean, reusable diagrams for papers
- Blog writers explaining ML concepts with visuals
- Educators building teaching slides on neural network topics
Not ideal for
- Anyone needing software or code, since the project is a set of slides rather than a program
- People who need figures for non-ML topics, because the collection is focused on machine learning
- Users who need a stable, versioned asset library, since the README mentions only Version 1.0 and the last push was in February 2023
How to get it
- 1
Read it online
Clone the repository
git clone https://github.com/dair-ai/ml-visuals - 2
Run it
- Open the Version 1.0 Google Slides link from the README
- Browse the slides to find a figure that fits your needs
- Use File, Download, then choose a format to save a figure
- Check the slide notes for author credit before reuse
- 3
Get the most out of it
- Read the slide notes for author information and a short description of each visual
- Use the planned topic list in the README as a guide to what might be added later
- Request edit access from the Google Slides toolbar if you want to contribute
- Join the Discord or Slack community mentioned in the README for updates
Downloads
Strengths
- Free to use, with no permission needed according to the README; credit to the author is requested
- Figures are editable in Google Slides, so they can be customized
- Community-contributed, with a list of planned topics such as transformers, LSTMs, and ResNet
Trade-offs
- Relies on Google Slides, so editing requires Google access and requesting edit permission
- The README says updates are coming but the last push date is February 2023, so the collection may not be current
- Contributor attribution depends on notes in each slide, which is easy to miss
How it compares
| Project | Stars | Type | Level | Updated | Best for |
|---|---|---|---|---|---|
| ml-visuals (this) | 17.4k | Other | beginner | 3.7 years ago | Machine learning students preparing presentations or thesis figures |
| excalidraw | 135k | App | beginner | 4 days ago | Teams sketching diagrams or wireframes together in a shared canvas |
| mermaid | 91k | Dev tool | beginner | 4 days ago | Developers who want diagrams stored as text alongside their code and docs |
| AI-For-Beginners | 70.5k | Learning resource | beginner | 13 days ago | Beginners who want a structured, self-paced introduction to AI |
| Made-With-ML | 49.9k | Learning resource | intermediate | 8 months ago | Software engineers who want to learn how ML models get deployed and maintained |
| AI-Expert-Roadmap | 31.3k | Learning resource | beginner | 1.2 years ago | Beginners who are unsure what to learn next in AI or data science |
Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.