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yanshengjia/ml-road

Machine Learning and Agentic AI Resources, Practice and Research

Latest metrics (snapshot 2026-10-14)

stars4960
forks1723
issues7
pushed_at2026-08-01T12:36:17Z

History

History chart: 1 daily snapshot so far (archive started 2026-10-14). The line fills in as the daily archive grows; full series via the API.

DateGitHub stars
2026-10-144960

ADC Momentum: 2/100

ADC Momentum 2 Leaderboard

Growth velocity3
Consistency2
Recency3
Agent demand0
Basisbootstrap

ADC Momentum (0-100) = 45% growth velocity (stars/likes gained per day in our daily archive, relative and absolute, percentile-ranked within the category) + 20% consistency (share of recent days with growth) + 20% recency (latest push/update/release, decaying) + 15% agent demand (how often AI agents looked it up via our API/MCP this week). MCP servers use release cadence; LLMs use price cuts, context and recency. Recomputed daily; scores marked "bootstrap" use lifetime rates until the archive has enough days. Method

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Details

descriptionMachine Learning and Agentic AI Resources, Practice and Research
urlhttps://github.com/yanshengjia/ml-road
languagePython
licenseMIT
topicsagentic-ai
computer-vision
deep-learning
machine-learning
nlp
pytorch
speech-recognition
tensorflow
created_at2017-10-31T04:36:37Z

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