# loveunk/deep-learning-llm-agent-notes

机器学习、深度学习的学习路径及知识总结

Repository: https://github.com/loveunk/deep-learning-llm-agent-notes
Canonical: https://ross.abutalabs.com/products/deep-learning-llm-agent-notes
Homepage: https://loveunk.github.io/deep-learning-llm-agent-notes/
Language: Jupyter Notebook
License Family: other
Last push: 2026-06-27T23:08:14+00:00

## Health v2 (maintenance only)
Score: 72/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 89, release rhythm 35, longevity 100
- inputs: {"age_days": 2772, "days_push": 67, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2698, forks 406 (observed 2026-08-28T04:07:11.263550+00:00)

## What it is
A Chinese-language learning roadmap and knowledge repository covering machine learning, deep learning, and large language model engineering, organized as structured paths from beginner to LLM/Agent engineering. It includes Jupyter Notebook materials and curated guides on RAG, prompting, fine-tuning, tool calling, and agent productionization.

## Use cases
- learn machine learning from scratch in 30 days
- roadmap to become an LLM engineer
- learn how to build RAG applications
- understand AI agent tool calling and workflows
- review deep learning fundamentals like CNN and RNN
- learn prompt engineering and fine-tuning with LoRA
- find a structured AI study path in Chinese

## When to choose
- you want a curated, practice-first learning path for AI/ML and LLM engineering
- you prefer Chinese-language explanations and structured roadmaps
- you want to move from chatbot basics to agent systems with tool calling and guardrails

## When to avoid
- you need production-ready software or a runnable framework rather than study notes
- you need English-language or formally peer-reviewed course material
- you require a licensed or citable resource, since the repo has no license

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools
- domain: machine-learning, deep-learning, large-language-models, tutorials
- platform: python, cross-platform
- tags: learning-roadmap, chinese-language, jupyter-notebooks, llm-engineering, study-guide, rag, prompt-engineering, fine-tuning, retrieval-augmented-generation, ai-agents

## Member repositories
- loveunk/deep-learning-llm-agent-notes (main) score 72

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:11.263550+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:16:08.821824+00:00, confidence not recorded.
  - readme: https://github.com/loveunk/deep-learning-llm-agent-notes (fetched 2026-08-28T04:07:11.263550+00:00, sha 6b365337d9de)
  - homepage: https://loveunk.github.io/deep-learning-llm-agent-notes/ (fetched 2026-08-29T09:59:13.845804+00:00, sha 99d4ea123e2d)
- Data as of 2026-08-30T08:39:29.467469+00:00.