# xiaqunfeng/machine-learning-yearning

Translation of <Machine Learning Yearning> by Andrew NG

Repository: https://github.com/xiaqunfeng/machine-learning-yearning
Canonical: https://ross.abutalabs.com/products/machine-learning-yearning
License: CC-BY-SA-4.0
License Family: other
Last push: 2023-08-19T03:13:56+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": 3157, "days_push": 1110, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1334, forks 402 (observed 2026-08-28T04:04:24.875321+00:00)

## What it is
A Chinese translation of Andrew Ng's book 'Machine Learning Yearning', covering all 58 chapters on how to organize and make decisions in machine learning projects. The translation is hosted on GitBooks and includes the original English draft PDFs.

## Use cases
- learn machine learning project strategy in Chinese
- read Machine Learning Yearning translation
- understand how to set up train/dev/test sets
- learn error analysis and bias-variance tradeoff
- study when to use end-to-end deep learning
- compare model performance to human-level performance

## When to choose
- you prefer reading Andrew Ng's ML guidance in Chinese
- you want practical advice on structuring ML projects
- you need the original English drafts alongside a translation

## When to avoid
- you need a hands-on coding tutorial or code library
- you want up-to-date ML techniques beyond the 2018 manuscript
- you need an interactive course rather than a book

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, machine-learning
- domain: machine-learning, tutorials, education
- platform: -
- tags: book-translation, chinese-translation, andrew-ng, deep-learning, gitbook, machine-learning-yearning, web-server

## Member repositories
- xiaqunfeng/machine-learning-yearning (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:24.875321+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 2026-08-30T04:44:36.290875+00:00, confidence not recorded.
  - readme: https://github.com/xiaqunfeng/machine-learning-yearning (fetched 2026-08-28T04:04:24.875321+00:00, sha a290eb1f988e)
- Data as of 2026-08-30T08:39:29.467469+00:00.