# OUCMachineLearning/OUCML

Repository: https://github.com/OUCMachineLearning/OUCML
Canonical: https://ross.abutalabs.com/products/oucml
Language: Python
License Family: other
Last push: 2020-09-14T02:59:36+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2836, "days_push": 2179, "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 4598, forks 1294 (observed 2026-08-28T04:08:54.804162+00:00)

## What it is
A curated collection of machine learning and deep learning study materials, most notably the 'One Day One GAN' (ODOG) series of GAN implementations, plus AutoML resources. It serves as a learning-oriented repository of code examples rather than a production library.

## Use cases
- learn how GAN variants are implemented in PyTorch
- study one GAN paper implementation per day
- find AutoML example code and references
- use as reference code when reimplementing deep learning papers
- explore generative adversarial network architectures

## When to choose
- you want readable educational implementations of GANs
- you are studying deep learning and want curated code examples
- you need reference implementations to accompany reading papers

## When to avoid
- you need a production-ready, maintained ML framework
- you require a license for commercial use (none is provided)
- you need actively updated code - the repo has not seen releases since 2020

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: deep-learning, machine-learning, tutorials
- platform: python
- tags: gan, automl, study-collection, educational, paper-implementations

## Member repositories
- OUCMachineLearning/OUCML (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:54.804162+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 2026-08-29T18:19:48.320808+00:00, confidence not recorded.
  - readme: https://github.com/OUCMachineLearning/OUCML (fetched 2026-08-28T04:08:54.804162+00:00, sha 41f48aa5b863)
- Data as of 2026-08-30T08:39:29.467469+00:00.