# Visualize-ML/Book7_Visualizations-for-Machine-Learning

Book_7_《机器学习》 |   鸢尾花书：从加减乘除到机器学习；欢迎批评指正

Repository: https://github.com/Visualize-ML/Book7_Visualizations-for-Machine-Learning
Canonical: https://ross.abutalabs.com/products/book7_visualizations-for-machine-learning
Language: Jupyter Notebook
License Family: other
Topics: baysian, data-science, linear-algebra, machine-learning, machine-learning-algorithms, matrix
Last push: 2026-05-01T14:41:33+00:00

## Health v2 (maintenance only)
Score: 68/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 80, release rhythm 35, longevity 100
- inputs: {"age_days": 1423, "days_push": 124, "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 3344, forks 628 (observed 2026-08-28T04:07:56.996630+00:00)

## What it is
Book7 of the 'Iris' book series (鸢尾花书), an open-source Chinese-language machine-learning textbook built from Jupyter notebooks that teach ML concepts from basic arithmetic through linear algebra to algorithms via extensive visualizations. It complements earlier volumes on statistics, math essentials, and matrix algebra.

## Use cases
- learn machine learning fundamentals with visual explanations
- study linear algebra and matrices for ML
- understand Bayesian methods through plots
- find runnable Jupyter notebook examples for ML algorithms
- supplement a math-for-ML self-study curriculum
- teach data science with visualization-first materials

## When to choose
- you prefer learning ML through intuition and visualizations rather than heavy theory
- you read Chinese and want a free, notebook-based ML course
- you need to refresh linear algebra and probability before ML

## When to avoid
- you need production ML code or a maintained library
- you require an English-language resource
- you need a formally licensed, citable textbook (no license is attached)

## Facets
- artifact type: learning-resource
- maturity: active
- function: data-visualization, machine-learning, math
- domain: machine-learning, data-science, education, tutorials, data-visualization
- platform: python, cross-platform
- tags: jupyter-notebooks, chinese-language, iris-book-series, linear-algebra, bayesian, visualization-driven-learning

## Member repositories
- Visualize-ML/Book7_Visualizations-for-Machine-Learning (main) score 68

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:56.996630+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 2026-08-29T18:41:01.690817+00:00, confidence not recorded.
  - readme: https://github.com/Visualize-ML/Book7_Visualizations-for-Machine-Learning (fetched 2026-08-28T04:07:56.996630+00:00, sha 32a90ffacfaf)
- Data as of 2026-08-30T08:39:29.467469+00:00.