# dair-ai/ml-visuals

🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

Repository: https://github.com/dair-ai/ml-visuals
Canonical: https://ross.abutalabs.com/products/ml-visuals
License: MIT
License Family: permissive
Topics: machine-learning, deep-learning, natural-language-processing, artificial-intelligence, design
Last push: 2023-02-13T22:23:17+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2299, "days_push": 1297, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 17378, forks 1553 (observed 2026-08-28T04:11:19.607439+00:00)

## What it is
A collaborative collection of over 100 free, reusable machine learning figures and templates maintained in Google Slides by the dair.ai community. It helps researchers, students, and bloggers improve science communication with professional visuals they can copy and customize.

## Use cases
- find figures for a machine learning paper or thesis
- create visuals for an ML presentation or talk
- customize diagrams for a technical blog post
- reuse neural network and NLP diagrams in slides
- contribute open-source ML illustrations to the community

## When to choose
- you need ready-made, customizable ML diagrams without drawing them yourself
- you want openly licensed figures for papers, blogs, or presentations
- you prefer editing visuals in Google Slides

## When to avoid
- you need programmatically generated or code-driven figures
- you require visuals outside machine learning topics
- you need a tool rather than a slide-based asset collection

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-visualization, documentation
- domain: machine-learning, deep-learning, education, data-visualization
- platform: cross-platform
- tags: google-slides, figures, templates, science-communication, presentations, open-contributions, natural-language-processing, web-server

## Member repositories
- dair-ai/ml-visuals (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:19.607439+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:03:01.272894+00:00, confidence not recorded.
  - readme: https://github.com/dair-ai/ml-visuals (fetched 2026-08-28T04:11:19.607439+00:00, sha c3aaebbaf08d)
- Data as of 2026-08-30T08:39:29.467469+00:00.