# fengdu78/machine_learning_beginner

机器学习初学者公众号作品

Repository: https://github.com/fengdu78/machine_learning_beginner
Canonical: https://ross.abutalabs.com/products/machine_learning_beginner
Language: Jupyter Notebook
License Family: other
Last push: 2021-03-21T15:42:14+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": 2793, "days_push": 1991, "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 2353, forks 913 (observed 2026-08-28T04:06:40.549048+00:00)

## What it is
A collection of Jupyter Notebook tutorials and curated articles from the 'Machine Learning Beginner' WeChat public account, covering Python, NumPy, pandas, matplotlib, scikit-learn, PyTorch, and deep learning basics in Chinese. It serves as a structured learning path for students and newcomers entering AI and machine learning.

## Use cases
- learn machine learning from scratch as a beginner
- find a structured AI learning roadmap with resources
- learn Python, NumPy, and pandas quickly with notebooks
- get Chinese translations of PyTorch and deep learning tutorials
- study scikit-learn with classic example cases
- supplement coursework with machine learning study notes

## When to choose
- you are a Chinese-speaking beginner wanting a curated, step-by-step ML learning path
- you prefer learning through runnable Jupyter notebooks
- you want free translations of popular deep learning book code and PyTorch tutorials

## When to avoid
- you need production-ready machine learning code or libraries
- you require a maintained project with a license or active updates
- you are an advanced practitioner looking for cutting-edge research material

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, data-science, nlp
- domain: machine-learning, deep-learning, data-science, tutorials, education
- platform: python, cross-platform
- tags: jupyter-notebooks, chinese-language, beginner-friendly, pytorch, tensorflow, numpy, pandas, sklearn, wechat-publication

## Member repositories
- fengdu78/machine_learning_beginner (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:40.549048+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 2026-08-30T02:36:29.716946+00:00, confidence not recorded.
  - readme: https://github.com/fengdu78/machine_learning_beginner (fetched 2026-08-28T04:06:40.549048+00:00, sha dfc77f5d8d28)
- Data as of 2026-08-30T08:39:29.467469+00:00.