HandsOnLLM/Hands-On-Large-Language-Models — GitHub trend

◂ BACK TO LEADERBOARD

FINDING #4834 · UNIT ID 821372392

HandsOnLLM/Hands-On-Large-Language-Models

Official code repo for the O'Reilly Book - "Hands-On Large Language Models"

[ JUPYTER NOTEBOOK ][ ORG ][ GITHUB ↗ ]

SURPRISE SCORE

0.00

Score Breakdown

SURPRISE0.00358

ENGAGEMENT0.44

FRESHNESS1.46

SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE

SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)

3% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D

27.73

ACCEL

+1.12

RETENTION

45.5%

PEAK 2026-08-11 · FORK-RETENTION 57.7% · 832 STARS / WINDOW

Author Audience

AUDIENCE

7,715

FOLLOWERS

985

OWNER ★

28,724

Engagement Signals

FORKS

6,591

ISSUE AUTH

PR AUTH

UNIQUE STARGAZERS 832 / 832 (DIVERSITY 1.00)

Why This Is A Finding

HandsOnLLM/Hands-On-Large-Language-Models собрал 832 звёзд за окно, тогда как у автора всего 985 подписчиков — эффективная аудитория ≈ 7,715. Это даёт surprise-индекс 0.00358 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 57.7% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.

Related Findings

RANKS ABOVE 50% OF 9591 FINDINGS

#195xbsheng/atguigu-note[ JUPYTER NOTEBOOK ]0.0835 #329lyogavin/airllm[ JUPYTER NOTEBOOK ]0.0381 #347gmonce/scikit-learn-book[ JUPYTER NOTEBOOK ]0.0371 #564raiyanyahya/how-to-train-your-gpt[ JUPYTER NOTEBOOK ]0.029 #874Mengmouxu/SceneGen[ JUPYTER NOTEBOOK ]0.0224

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9591 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW

METRICVALUEMEDIANΔ MEDPERCENTILE

SCORE0.000.00-0.00ABOVE 50%

VELOCITY27.733.63+24.10ABOVE 93%

RETENTION45.5%24.8%+20.7 PPABOVE 86%

FORKS6,591120+6,471ABOVE 99%

SURPRISE0.000.01-0.00ABOVE 31%