# mossr/BeautifulAlgorithms.jl

Concise and beautiful algorithms written in Julia

Repository: https://github.com/mossr/BeautifulAlgorithms.jl
Canonical: https://ross.abutalabs.com/products/beautifulalgorithmsjl
Language: Julia
License Family: other
Topics: algorithms, machine-learning, optimization, sorting, quine, julia, reinforcement-learning, decision-making-under-uncertainty, regression, neural-network
Last push: 2025-03-04T19:43:57+00:00

## Health v2 (maintenance only)
Score: 36/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 9, release rhythm 35, longevity 100
- inputs: {"age_days": 2178, "days_push": 547, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1426, forks 97 (observed 2026-08-28T04:04:41.651191+00:00)

## What it is
A collection of concise, self-contained algorithm implementations in Julia covering machine learning, optimization, reinforcement learning, and sorting. It is intended for academic and educational purposes rather than production use.

## Use cases
- learn how classic algorithms are implemented in julia
- study machine learning algorithm implementations from scratch
- find concise examples of gradient descent and neural networks
- learn reinforcement learning algorithms like monte carlo tree search
- reference implementations of sorting algorithms
- teach algorithms in a course with readable code

## When to choose
- you want short, readable, self-contained algorithm implementations for learning or teaching
- you are studying machine learning, optimization, or decision-making under uncertainty
- you prefer Julia as the language for algorithm study

## When to avoid
- you need production-ready, performant, or well-tested algorithm libraries
- you need a package with a maintained license and API stability guarantees
- you need comprehensive, optimized implementations of these algorithms

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, reinforcement-learning, math, developer-tools
- domain: machine-learning, education, programming-languages
- platform: -
- tags: julia, algorithms, educational, reinforcement-learning, optimization, sorting, academic

## Member repositories
- mossr/BeautifulAlgorithms.jl (main) score 36

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:41.651191+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 2026-08-30T04:37:27.660972+00:00, confidence not recorded.
  - readme: https://github.com/mossr/BeautifulAlgorithms.jl (fetched 2026-08-28T04:04:41.651191+00:00, sha 33474b976983)
- Data as of 2026-08-30T08:39:29.467469+00:00.