Github Trends®
9593 findingsmedian surprise 0.00799window 30 days
UNIT / TREND-MONITOR · REV 2.6
[ 30 days window ]
SOURCE: own snapshots
FINDING #8808 · UNIT ID 1083330204
ai-infra-curriculum/ai-infra-engineer-learning
AI Infrastructure Engineer Learning Track - Production ML infrastructure curriculum (2-4 years experience)
[ PYTHON ][ ORG ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.00306
ENGAGEMENT0.52
FRESHNESS1.31
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
5% OF STARS IN ARCHIVE
[BOT] SUSPECTED STAR BOT — SCORE PENALIZED. SIGNATURES:
S2 · NO EXTERNAL ISSUE/PR AUTHORS DESPITE 100+ STARS
S10 · DEAD CODE, ZERO CONTRIBUTORS, YET STARS KEEP DRIPPING

Growth Telemetry

VELOCITY /D
2.87
ACCEL
+0.01
RETENTION
26.7%
PEAK 2026-08-12 · FORK-RETENTION 35.3% · 86 STARS / WINDOW

Author Audience

AUDIENCE
897
FOLLOWERS
246
OWNER ★
2,025

Engagement Signals

FORKS
280
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 86 / 86 (DIVERSITY 1.00)

Why This Is A Finding

ai-infra-curriculum/ai-infra-engineer-learning собрал 86 звёзд за окно, тогда как у автора всего 246 подписчиков — эффективная аудитория ≈ 897. Это даёт surprise-индекс 0.00306 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 35.3% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9593 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 8%
VELOCITY2.873.63-0.77ABOVE 39%
RETENTION26.7%25.0%+1.7 PPABOVE 53%
FORKS280117+163ABOVE 71%
SURPRISE0.000.01-0.00ABOVE 28%