FINDING #2975 · UNIT ID 1213864838
Elite588/machine-learning-for-trading
This book aims to show how ML can add value to algorithmic trading strategies in a practical yet comprehensive way. It covers a broad range of ML techniques from linear regression to deep reinforcement learning and demonstrates how to build, backtest, and evaluate a trading strategy driven by model predictions.
SURPRISE SCORE
0.00
Score Breakdown
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
10% OF STARS IN ARCHIVE
Growth Telemetry
VELOCITY /D
14.00
ACCEL
0.00
RETENTION
0.0%
PEAK 2026-09-24 · FORK-RETENTION 0.0% · 14 STARS / WINDOW
Author Audience
AUDIENCE
2,864
FOLLOWERS
2,786
OWNER ★
781
Engagement Signals
FORKS
11
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 14 / 14 (DIVERSITY 1.00)
Why This Is A Finding
Elite588/machine-learning-for-trading собрал 14 звёзд за окно, тогда как у автора всего 2,786 подписчиков — эффективная аудитория ≈ 2,864. Это даёт surprise-индекс 0.00482 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.
Related Findings
RANKS ABOVE 49% OF 5833 FINDINGS
METRICS IN CONTEXT
MEDIAN ACROSS ALL 5833 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 49%
VELOCITY14.009.00+5.00ABOVE 65%
RETENTION0.0%0.0%0.0 PPABOVE 0%
FORKS11419-408ABOVE 6%
SURPRISE0.000.01-0.00ABOVE 47%