# Vay-keen/Machine-learning-learning-notes

周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！

Repository: https://github.com/Vay-keen/Machine-learning-learning-notes
Canonical: https://ross.abutalabs.com/products/machine-learning-learning-notes
License Family: other
Last push: 2022-02-26T17:19:34+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": 3084, "days_push": 1649, "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 7764, forks 1880 (observed 2026-08-28T04:10:04.843074+00:00)

## What it is
A set of Chinese-language study notes for Zhou Zhihua's machine learning textbook (the 'Watermelon Book'), covering supervised, unsupervised, semi-supervised, and reinforcement learning, ensemble methods, dimensionality reduction, and feature selection. It supplements the book with the author's explanations and extended knowledge points to help newcomers.

## Use cases
- study the watermelon book machine learning textbook
- learn machine learning algorithms from scratch
- understand supervised and unsupervised learning concepts
- find supplementary explanations for Zhou Zhihua's ML book
- prepare for machine learning interviews
- review statistical learning methods alongside Li Hang's book

## When to choose
- you are reading the Watermelon Book and want companion notes in Chinese
- you are a beginner wanting structured explanations of classic ML algorithms
- you want free community-maintained study material with a discussion group

## When to avoid
- you need runnable code or production ML tooling
- you prefer English-language learning resources
- you need up-to-date content on deep learning or LLMs

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, nlp, data-science
- domain: machine-learning, tutorials, data-science
- platform: cross-platform
- tags: study-notes, watermelon-book, chinese-language, machine-learning-algorithms, textbook-companion

## Member repositories
- Vay-keen/Machine-learning-learning-notes (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:04.843074+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 2026-08-29T17:35:07.897260+00:00, confidence not recorded.
  - readme: https://github.com/Vay-keen/Machine-learning-learning-notes (fetched 2026-08-28T04:10:04.843074+00:00, sha 8aba2c8f757b)
- Data as of 2026-08-30T08:39:29.467469+00:00.