# helblazer811/ManimML

ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

Repository: https://github.com/helblazer811/ManimML
Canonical: https://ross.abutalabs.com/products/manimml
Language: Python
License: MIT
License Family: permissive
Topics: machine-learning, neural-network, visualization, manim, 3blue1brown
Last push: 2024-06-22T19:22:15+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1673, "days_push": 802, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3492, forks 220 (observed 2026-08-28T04:08:07.222125+00:00)

## What it is
ManimML is a Python library built on the Manim Community Library for creating animations and visualizations of machine learning concepts like neural networks and convolutional layers. It provides reusable primitives and abstractions so users can compose explanatory videos without low-level software engineering.

## Use cases
- animate a convolutional neural network forward pass for a lecture video
- visualize max pooling and activation functions in a tutorial
- create 3Blue1Brown-style explainer videos about deep learning
- render neural network architecture diagrams as animations
- teach machine learning concepts with animated visualizations
- build custom ML concept animations from reusable primitives

## When to choose
- you need animated, programmatic visualizations of ML concepts for teaching or videos
- you already use Manim and want neural network building blocks
- you want reproducible, code-driven educational animations

## When to avoid
- you need interactive or real-time visualization rather than rendered video
- you want plotting of actual training data or model metrics
- you need a no-code diagramming tool

## Facets
- artifact type: library
- maturity: active
- function: data-visualization, animation, machine-learning
- domain: machine-learning, data-visualization, education, deep-learning
- platform: python, cross-platform
- tags: manim, neural-networks, educational-animations, 3blue1brown, video-rendering

## Member repositories
- helblazer811/ManimML (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:07.222125+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 2026-08-29T18:35:56.670826+00:00, confidence not recorded.
  - readme: https://github.com/helblazer811/ManimML (fetched 2026-08-28T04:08:07.222125+00:00, sha faa96f76cd6a)
- Data as of 2026-08-30T08:39:29.467469+00:00.