Github Trends®
9757 findingsmedian surprise 0.00913window 7 days
UNIT / TREND-MONITOR · REV 2.6
[ 7 days window ]
SOURCE: own snapshots
FINDING #1305 · UNIT ID 1337390717
zorost/AI-Engineering-Lab
A free, self-paced 24-week AI engineering course: Python, machine learning, LLMs, RAG, fine-tuning, agents and MCP, Azure and Vertex and Bedrock, and Databricks. 43 runnable notebooks, one continuous case study. MIT licensed, no signup. By Zorost Intelligence AI Lab.
[ JUPYTER NOTEBOOK ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.0187
ENGAGEMENT0.82
FRESHNESS1.00
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
19% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D
3.29
ACCEL
+1.89
RETENTION
83.3%
PEAK 2026-08-24 · FORK-RETENTION 45.5% · 23 STARS / WINDOW

Author Audience

AUDIENCE
136
FOLLOWERS
114
OWNER ★
216

Engagement Signals

FORKS
114
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 23 / 23 (DIVERSITY 1.00)

Why This Is A Finding

zorost/AI-Engineering-Lab собрал 23 звёзд за окно, тогда как у автора всего 114 подписчиков — эффективная аудитория ≈ 136. Это даёт surprise-индекс 0.0187 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 45.5% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9757 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.010.00+0.01ABOVE 87%
VELOCITY3.293.71-0.43ABOVE 45%
RETENTION83.3%37.5%+45.8 PPABOVE 96%
FORKS11492+22ABOVE 55%
SURPRISE0.020.01+0.01ABOVE 68%