# fengdu78/Data-Science-Notes

数据科学的笔记以及资料搜集

Repository: https://github.com/fengdu78/Data-Science-Notes
Canonical: https://ross.abutalabs.com/products/data-science-notes
Language: Jupyter Notebook
License Family: other
Last push: 2021-08-16T11:18:41+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": 2592, "days_push": 1843, "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 8581, forks 3108 (observed 2026-08-28T04:10:23.638143+00:00)

## What it is
A collection of Jupyter Notebook study notes and curated resources covering the data science stack, from math and Python basics through NumPy, pandas, scikit-learn, machine learning, deep learning, and feature engineering. Content is primarily in Chinese and compiled from the author's own notes plus aggregated GitHub resources.

## Use cases
- learn data science from scratch with jupyter notebooks
- study machine learning basics in chinese
- find notes on numpy pandas and scikit-learn
- review deep learning fundamentals
- learn feature engineering techniques
- get a data science learning roadmap

## When to choose
- you prefer Chinese-language study materials
- you want notebook-based tutorials spanning the full data science pipeline
- you need curated links to quality ML learning resources

## When to avoid
- you need production-ready code or maintained libraries
- you require English-only materials
- you need content guaranteed to be up to date

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, machine-learning, deep-learning, data-visualization
- domain: data-science, machine-learning, deep-learning, tutorials
- platform: python, cross-platform
- tags: jupyter-notebooks, study-notes, chinese-language, numpy, pandas, scikit-learn, feature-engineering

## Member repositories
- fengdu78/Data-Science-Notes (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:23.638143+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 2026-08-29T17:26:15.695818+00:00, confidence not recorded.
  - readme: https://github.com/fengdu78/Data-Science-Notes (fetched 2026-08-28T04:10:23.638143+00:00, sha f5d635b56e1f)
- Data as of 2026-08-30T08:39:29.467469+00:00.