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#37 · Top 3.4%

afshinea

Afshine Amidi

Ecole Centrale Paris, MIT

B

Solid engineer

Overall

74.7

/ 100

Roasts

The syllabus that escaped

You made machine learning look so organized that the repository name practically arrives with office hours, prerequisites, and a midterm it expects us to grade ourselves.

Transformer season pass

The transformer repository has the energy of someone arriving at the AI frontier with a clipboard, a reading list, and absolutely no intention of letting the hype cycle finish first.

Diffusion with a deadline

A repository about diffusion and large vision models is a wonderfully ambitious choice: even the project premise sounds like it is still spreading into new territory.

The data plumbing specialist

After surveying the grand landscape of AI, you also kept a dedicated Keras data generator around to remind every glamorous model that someone still has to feed it.

Category breakdown

afshinea category score radarImpactConsistencyQualityDepthBreadthCommunity

Consistency

76

The portfolio shows multiple substantial repositories, with activity spanning 2018 through 2026 and recent updates on advanced machine-learning topics. The supplied dates do not establish continuous maintenance, so this is strong but not at

Impact

88

The projects center on structured educational material for deep learning, machine learning, artificial intelligence, transformers, and diffusion models, plus a practical Keras utility. This is a coherent and potentially highly useful body

Quality

62

Repository scope and focused subject areas provide positive maturity signals, but the evidence omits source, tests, documentation, architecture, licensing, and implementation details. The score therefore reflects credible project framing

Breadth

57

The portfolio covers several major AI and machine-learning areas and includes Python in one repository. Language metadata is unavailable for the other repositories, and the projects remain concentrated within one technical domain.

Depth

82

Six non-fork, non-archived repositories include several sizable course-oriented subjects and specialized modern-model topics. The sustained thematic ownership is strong, though implementation depth cannot be verified from metadata alone.

Community

74

The repositories show substantial public interest and the profile has many followers, which is a weak positive signal for community reach. Popularity is not used to raise the other category scores, and community evidence remains incomplete.

Stats

52-week commit heatmap

1 active days

Language distribution

  • Unknown83%
  • Python17%

Based on the bounded repository sample saved with this analysis.

Numbers

6

Public repos

4618

Followers

2

Commits

1

History

Top repos

afshinea/stanford-cs-230-deep-learning

79

A focused Stanford CS 230 deep-learning resource with sustained public interest and a clear educational purpose; implementation and maintenance quality cannot be assessed from the supplied metadata.

Unknown · ★ 7056

afshinea/stanford-cs-229-machine-learning

84

A substantial machine-learning course repository with a clear, broad educational scope and strong public reach; the available evidence does not reveal its internal completeness or engineering practices.

Unknown · ★ 20059

afshinea/stanford-cme-295-transformers-large-language-models

82

A specialized repository centered on transformers and large language models, indicating timely subject focus and ambitious scope; recent activity is visible, but project maturity beyond metadata is unknown.

Unknown · ★ 4630

afshinea/stanford-cme-296-diffusion-large-vision-models

68

A focused repository on diffusion and large vision models with recent activity and a specialized premise; its relatively limited visible history leaves completion and depth uncertain.

Unknown · ★ 132

afshinea/stanford-cs-221-artificial-intelligence

77

An artificial-intelligence course repository with a coherent educational scope and meaningful public reach; details of contents and implementation are unavailable.

Unknown · ★ 2978

afshinea/keras-data-generator

55

A practical Python Keras data-generator project with a concrete utility premise; it is older and narrower than the course repositories, while its public metadata indicates a focused, narrow scope.

Python · ★ 307

Timeline

No accepted timeline events were saved.

Compare

AFSHINEA · 6DMEDIAN CODER

AFSHINEA compared with MEDIAN CODER across six rating categoriesImpactConsistencyQualityDepthBreadthCommunity

Rubric

How this score was produced

This page renders one accepted, subject-bound rating-rubric/3 result from the immutable public U1 release. Missing evidence is kept unavailable instead of inferred.

Scores are not a security audit, endorsement, or guarantee of current repository behavior.

Rated 2026-08-09 · rating-rubric/3 · aging