# datawhalechina/team-learning

主要展示Datawhale的组队学习计划。

Repository: https://github.com/datawhalechina/team-learning
Canonical: https://ross.abutalabs.com/products/team-learning
License Family: other
Last push: 2023-01-08T13:37:15+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": 2437, "days_push": 1333, "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 2408, forks 692 (observed 2026-08-28T04:06:44.261932+00:00)

## What it is
A repository of Datawhale's team-based learning plans, listing cohort schedules, curricula, and links to open-source course materials on machine learning, computer vision, recommender systems, and design patterns. It serves as the central index for joining group study sessions with check-in and community Q&A.

## Use cases
- find machine learning study courses
- join a group learning program for OpenCV
- learn the watermelon book with a study group
- study design patterns with peers
- find free open-source AI curricula
- learn recommender systems from papers

## When to choose
- you want structured, cohort-based learning with community accountability
- you prefer free open-source Chinese-language ML and CV curricula
- you want guided schedules with check-ins and Q&A

## When to avoid
- you need production software or code libraries
- you want self-paced content without community interaction
- you need English-language materials only

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, developer-tools
- domain: machine-learning, computer-vision, education, tutorials, data-science
- platform: cross-platform
- tags: team-learning, study-plans, open-source-curriculum, chinese, datawhale, peer-learning

## Member repositories
- datawhalechina/team-learning (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:44.261932+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 2026-08-30T02:34:03.389201+00:00, confidence not recorded.
  - readme: https://github.com/datawhalechina/team-learning (fetched 2026-08-28T04:06:44.261932+00:00, sha d1d948919b97)
- Data as of 2026-08-30T08:39:29.467469+00:00.