# zibuyu/research_tao

NLP研究入门之道

Repository: https://github.com/zibuyu/research_tao
Canonical: https://ross.abutalabs.com/products/research_tao
License: MIT
License Family: permissive
Last push: 2019-11-26T07:08:27+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2705, "days_push": 2472, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2069, forks 253 (observed 2026-08-28T04:06:10.294345+00:00)

## What it is
A Chinese-language open guide on how to get started with NLP research, written by a Tsinghua professor. It covers the academic community, reading papers, finding ideas, writing papers, and undergraduate research training.

## Use cases
- learn how to start NLP research
- how to read academic papers effectively
- how to write a research paper in NLP
- how to find research ideas and topics
- how undergraduates can begin research training
- advice for choosing an AI major and PhD advisor

## When to choose
- you are a student starting out in NLP or AI research
- you want guidance on academic writing, paper reading, and research methodology
- you prefer Chinese-language learning material

## When to avoid
- you want technical NLP algorithms or code implementations
- you need a comprehensive English-language textbook
- you seek hands-on deep learning framework tutorials

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, nlp
- domain: education, tutorials
- platform: cross-platform
- tags: research-guide, academic-writing, phd, chinese-language, natural-language-processing

## Member repositories
- zibuyu/research_tao (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:10.294345+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 2026-08-30T02:56:46.705026+00:00, confidence not recorded.
  - readme: https://github.com/zibuyu/research_tao (fetched 2026-08-28T04:06:10.294345+00:00, sha ef2714d43d95)
- Data as of 2026-08-30T08:39:29.467469+00:00.