Github Trends®
2559 findingsmedian surprise 0.00074window 180 days
UNIT / TREND-MONITOR · REV 2.6
[ 180 days window ]
SOURCE: gharchive
FINDING #929 · UNIT ID 802545117
Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies
This repository contains a curated collection of 300+ case studies from over 80 companies, detailing practical applications and insights into machine learning (ML) system design. The contents are organized to help you easily find relevant case studies based on industry or specific ML use cases.
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.00156
ENGAGEMENT0.53
FRESHNESS1.51
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
5% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D
2.77
ACCEL
-0.06
RETENTION
4.2%
PEAK 2026-01-31 · FORK-RETENTION 86.5% · 499 STARS / WINDOW

Author Audience

AUDIENCE
1,733
FOLLOWERS
593
OWNER ★
11,396

Engagement Signals

FORKS
1,666
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 499 / 499 (DIVERSITY 1.00)

Why This Is A Finding

Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies собрал 499 звёзд за окно, тогда как у автора всего 593 подписчиков — эффективная аудитория ≈ 1,733. Это даёт surprise-индекс 0.00156 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 86.5% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 2559 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00+0.00ABOVE 64%
VELOCITY2.772.88-0.11ABOVE 48%
RETENTION4.2%6.3%-2.1 PPABOVE 35%
FORKS1,6661,183+483ABOVE 59%
SURPRISE0.000.00+0.00ABOVE 63%