cbamls/AI_Tutorial resource
大厂发布的AI落地实践、顶尖实验室的最新论文、工业界的真实踩坑记录 observed · 2026-08-28
Health v2 · maintenance only
71/100
- Activity 86
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2829
- days_rel: n/a
- days_push: 85
- n_releases_24m: 0
Adoption not part of the score
3688 stars · 511 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
AIQ is a curated knowledge base and companion website aggregating high-quality AI/ML/big-data engineering content from major tech companies (FAANG, Alibaba, Meituan, ByteDance), research labs, and technical communities, updated daily. It focuses on real-world production experience, latest papers, and industry lessons learned rather than auto-generated encyclopedic content.
Use cases
- find real-world LLM deployment case studies from big tech
- keep up with the latest AI papers and model releases
- learn recommender system engineering practices from industry
- read production incident postmortems and lessons learned in AI
- discover curated AI tools and product directories
- study agent infrastructure and RAG engineering practices
When to choose
- you want curated, experience-driven AI engineering articles instead of raw tutorials
- you follow Chinese-language tech blogs from Alibaba, Meituan, Tencent, ByteDance and FAANG
- you need a daily-updated feed of AI industry practice and paper digests
When to avoid
- you need runnable code, libraries, or a software tool rather than reading material
- you require content under an open-source license (no license is provided)
- you need English-only resources or structured datasets
Facets
learning-resource · maturity active
developer-tools search-engine data-science artificial-intelligence machine-learning large-language-models tutorials awesome-lists cross-platform curated-resources engineering-blogs llm recommender-systems search-systems chinese-content daily-updates industry-practice ai-agents web-server
3 sources
- readme: https://github.com/cbamls/AI_Tutorial · fetched 2026-08-28 · aabc6fdf7a8e
- homepage: https://www.6aiq.com · fetched 2026-08-29 · e1c7d1c19c57
- site_page: https://www.6aiq.com/about · fetched 2026-08-29 · e9d46e0d3644
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| cbamls/AI_Tutorial | main | 71 |
For agents
markdown · JSON · MCP: product_card(name="cbamls/AI_Tutorial")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem